id sid tid token lemma pos cana-2813 1 1 communications communication NOUN cana-2813 1 2 on on ADP cana-2813 1 3 applied apply VERB cana-2813 1 4 nonlinear nonlinear ADJ cana-2813 1 5 analysis analysis NOUN cana-2813 1 6 issn issn NOUN cana-2813 1 7 : : PUNCT cana-2813 1 8 1074 1074 NUM cana-2813 1 9 - - PUNCT cana-2813 1 10 133x 133x NUM cana-2813 1 11 vol vol NOUN cana-2813 1 12 32 32 NUM cana-2813 1 13 no no NOUN cana-2813 1 14 . . PUNCT cana-2813 2 1 4s 4s NUM cana-2813 2 2 ( ( PUNCT cana-2813 2 3 2025 2025 NUM cana-2813 2 4 ) ) PUNCT cana-2813 2 5 270 270 NUM cana-2813 2 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 2 7 enhancing enhance VERB cana-2813 2 8 healthcare healthcare NOUN cana-2813 2 9 through through ADP cana-2813 2 10 metaheuristic metaheuristic PROPN cana-2813 2 11 based base VERB cana-2813 2 12 deep deep ADJ cana-2813 2 13 learning learning NOUN cana-2813 2 14 : : PUNCT cana-2813 2 15 microarray microarray NOUN cana-2813 2 16 gene gene NOUN cana-2813 2 17 expression expression NOUN cana-2813 2 18 image image NOUN cana-2813 2 19 classification classification NOUN cana-2813 2 20 model model NOUN cana-2813 2 21 b. b. PROPN cana-2813 2 22 shyamala shyamala PROPN cana-2813 2 23 gowri1 gowri1 PROPN cana-2813 2 24 , , PUNCT cana-2813 2 25 * * PROPN cana-2813 2 26 , , PUNCT cana-2813 2 27 s. s. PROPN cana-2813 2 28 anu anu PROPN cana-2813 2 29 h. h. PROPN cana-2813 2 30 nair2 nair2 PROPN cana-2813 2 31 , , PUNCT cana-2813 2 32 k. k. PROPN cana-2813 2 33 p. p. NOUN cana-2813 2 34 sanal sanal PROPN cana-2813 3 1 kumar3 kumar3 PROPN cana-2813 3 2 , , PUNCT cana-2813 3 3 s.kamalakkannan4 s.kamalakkannan4 VERB cana-2813 3 4 1,*research 1,*research NUM cana-2813 3 5 scholar scholar NOUN cana-2813 3 6 , , PUNCT cana-2813 3 7 department department NOUN cana-2813 3 8 of of ADP cana-2813 3 9 computer computer NOUN cana-2813 3 10 science science NOUN cana-2813 3 11 and and CCONJ cana-2813 3 12 engineering engineering NOUN cana-2813 3 13 , , PUNCT cana-2813 3 14 annamalai annamalai PROPN cana-2813 3 15 university university PROPN cana-2813 3 16 , , PUNCT cana-2813 3 17 annamalai annamalai PROPN cana-2813 3 18 nagar nagar PROPN cana-2813 3 19 , , PUNCT cana-2813 3 20 chidambaram chidambaram PROPN cana-2813 3 21 , , PUNCT cana-2813 3 22 tamil tamil PROPN cana-2813 3 23 nadu nadu PROPN cana-2813 3 24 , , PUNCT cana-2813 3 25 india india PROPN cana-2813 3 26 . . PUNCT cana-2813 4 1 2assistant 2assistant NUM cana-2813 4 2 professor professor NOUN cana-2813 4 3 , , PUNCT cana-2813 4 4 department department NOUN cana-2813 4 5 of of ADP cana-2813 4 6 computer computer NOUN cana-2813 4 7 science science NOUN cana-2813 4 8 and and CCONJ cana-2813 4 9 engineering engineering NOUN cana-2813 4 10 , , PUNCT cana-2813 4 11 faculty faculty NOUN cana-2813 4 12 of of ADP cana-2813 4 13 engineering engineering NOUN cana-2813 4 14 and and CCONJ cana-2813 4 15 technology technology NOUN cana-2813 4 16 , , PUNCT cana-2813 4 17 annamalai annamalai PROPN cana-2813 4 18 university university PROPN cana-2813 4 19 , , PUNCT cana-2813 4 20 ( ( PUNCT cana-2813 4 21 deputed depute VERB cana-2813 4 22 to to ADP cana-2813 4 23 wpt wpt PROPN cana-2813 4 24 , , PUNCT cana-2813 4 25 chennai chennai PROPN cana-2813 4 26 ) ) PUNCT cana-2813 4 27 , , PUNCT cana-2813 4 28 chennai chennai PROPN cana-2813 4 29 , , PUNCT cana-2813 4 30 india india PROPN cana-2813 4 31 . . PUNCT cana-2813 5 1 3assistant 3assistant NUM cana-2813 5 2 professor professor NOUN cana-2813 5 3 , , PUNCT cana-2813 5 4 department department NOUN cana-2813 5 5 of of ADP cana-2813 5 6 cs cs PROPN cana-2813 5 7 , , PUNCT cana-2813 5 8 rv rv PROPN cana-2813 5 9 government government NOUN cana-2813 5 10 arts arts PROPN cana-2813 5 11 college college PROPN cana-2813 5 12 , , PUNCT cana-2813 5 13 chengalpattu chengalpattu ADV cana-2813 5 14 , , PUNCT cana-2813 5 15 india india PROPN cana-2813 5 16 4associate 4associate PROPN cana-2813 5 17 professor professor NOUN cana-2813 5 18 , , PUNCT cana-2813 5 19 department department NOUN cana-2813 5 20 of of ADP cana-2813 5 21 information information NOUN cana-2813 5 22 technology technology NOUN cana-2813 5 23 , , PUNCT cana-2813 5 24 school school NOUN cana-2813 5 25 of of ADP cana-2813 5 26 computing compute VERB cana-2813 5 27 sciences science NOUN cana-2813 5 28 , , PUNCT cana-2813 5 29 ( ( PUNCT cana-2813 5 30 vistas vista NOUN cana-2813 5 31 ) ) PUNCT cana-2813 5 32 , , PUNCT cana-2813 5 33 chennai chennai PROPN cana-2813 5 34 , , PUNCT cana-2813 5 35 tamil tamil PROPN cana-2813 5 36 nadu nadu PROPN cana-2813 5 37 , , PUNCT cana-2813 5 38 india india PROPN cana-2813 5 39 1,*shyamalagowribalaraman@gmail.com 1,*shyamalagowribalaraman@gmail.com PROPN cana-2813 5 40 , , PUNCT cana-2813 5 41 2anu_jul@yahoo.co.in 2anu_jul@yahoo.co.in NUM cana-2813 5 42 , , PUNCT cana-2813 5 43 3sanalprabha@yahoo.co.in 3sanalprabha@yahoo.co.in NUM cana-2813 5 44 , , PUNCT cana-2813 5 45 4kannan.scs@velsuniv.ac.in 4kannan.scs@velsuniv.ac.in NUM cana-2813 5 46 article article NOUN cana-2813 5 47 history history NOUN cana-2813 5 48 : : PUNCT cana-2813 5 49 received receive VERB cana-2813 5 50 : : PUNCT cana-2813 5 51 22 22 NUM cana-2813 5 52 - - SYM cana-2813 5 53 09 09 NUM cana-2813 5 54 - - PUNCT cana-2813 5 55 2024 2024 NUM cana-2813 5 56 revised revise VERB cana-2813 5 57 : : PUNCT cana-2813 5 58 25 25 NUM cana-2813 5 59 - - SYM cana-2813 5 60 11 11 NUM cana-2813 5 61 - - PUNCT cana-2813 5 62 2024 2024 NUM cana-2813 5 63 accepted accept VERB cana-2813 5 64 : : PUNCT cana-2813 5 65 06 06 NUM cana-2813 5 66 - - SYM cana-2813 5 67 12 12 NUM cana-2813 5 68 - - PUNCT cana-2813 5 69 2024 2024 NUM cana-2813 5 70 abstract abstract NOUN cana-2813 5 71 : : PUNCT cana-2813 5 72 microarray microarray NOUN cana-2813 5 73 gene gene NOUN cana-2813 5 74 expression expression NOUN cana-2813 5 75 data datum NOUN cana-2813 5 76 analysis analysis NOUN cana-2813 5 77 has have AUX cana-2813 5 78 revolutionized revolutionize VERB cana-2813 5 79 genomics genomic NOUN cana-2813 5 80 by by ADP cana-2813 5 81 providing provide VERB cana-2813 5 82 insights insight NOUN cana-2813 5 83 into into ADP cana-2813 5 84 the the DET cana-2813 5 85 genetic genetic ADJ cana-2813 5 86 basis basis NOUN cana-2813 5 87 of of ADP cana-2813 5 88 diseases disease NOUN cana-2813 5 89 , , PUNCT cana-2813 5 90 including include VERB cana-2813 5 91 cancer cancer NOUN cana-2813 5 92 . . PUNCT cana-2813 6 1 however however ADV cana-2813 6 2 , , PUNCT cana-2813 6 3 the the DET cana-2813 6 4 high high ADJ cana-2813 6 5 dimensionality dimensionality NOUN cana-2813 6 6 of of ADP cana-2813 6 7 microarray microarray NOUN cana-2813 6 8 data datum NOUN cana-2813 6 9 poses pose VERB cana-2813 6 10 significant significant ADJ cana-2813 6 11 challenges challenge NOUN cana-2813 6 12 for for ADP cana-2813 6 13 accurate accurate ADJ cana-2813 6 14 classification classification NOUN cana-2813 6 15 , , PUNCT cana-2813 6 16 often often ADV cana-2813 6 17 leading lead VERB cana-2813 6 18 to to ADP cana-2813 6 19 overfitting overfitte VERB cana-2813 6 20 and and CCONJ cana-2813 6 21 poor poor ADJ cana-2813 6 22 generalization generalization NOUN cana-2813 6 23 . . PUNCT cana-2813 7 1 this this DET cana-2813 7 2 study study NOUN cana-2813 7 3 proposes propose VERB cana-2813 7 4 a a DET cana-2813 7 5 novel novel ADJ cana-2813 7 6 framework framework NOUN cana-2813 7 7 that that PRON cana-2813 7 8 integrates integrate VERB cana-2813 7 9 the the DET cana-2813 7 10 dna dna PROPN cana-2813 7 11 bidirectional bidirectional ADJ cana-2813 7 12 encoder encoder NOUN cana-2813 7 13 representations representation VERB cana-2813 7 14 from from ADP cana-2813 7 15 transformers transformer NOUN cana-2813 7 16 ( ( PUNCT cana-2813 7 17 dnabert dnabert NOUN cana-2813 7 18 ) ) PUNCT cana-2813 7 19 with with ADP cana-2813 7 20 the the DET cana-2813 7 21 mayfly mayfly NOUN cana-2813 7 22 optimization optimization NOUN cana-2813 7 23 algorithm algorithm NOUN cana-2813 7 24 ( ( PUNCT cana-2813 7 25 mfo mfo NOUN cana-2813 7 26 ) ) PUNCT cana-2813 7 27 to to PART cana-2813 7 28 improve improve VERB cana-2813 7 29 the the DET cana-2813 7 30 classification classification NOUN cana-2813 7 31 accuracy accuracy NOUN cana-2813 7 32 of of ADP cana-2813 7 33 microarray microarray NOUN cana-2813 7 34 gene gene NOUN cana-2813 7 35 expression expression NOUN cana-2813 7 36 data datum NOUN cana-2813 7 37 . . PUNCT cana-2813 8 1 dnabert dnabert PROPN cana-2813 8 2 , , PUNCT cana-2813 8 3 a a DET cana-2813 8 4 transformer transformer NOUN cana-2813 8 5 - - PUNCT cana-2813 8 6 based base VERB cana-2813 8 7 model model NOUN cana-2813 8 8 pretrained pretraine VERB cana-2813 8 9 on on ADP cana-2813 8 10 genomic genomic ADJ cana-2813 8 11 sequences sequence NOUN cana-2813 8 12 , , PUNCT cana-2813 8 13 excels excel NOUN cana-2813 8 14 in in ADP cana-2813 8 15 learning learn VERB cana-2813 8 16 complex complex ADJ cana-2813 8 17 gene gene NOUN cana-2813 8 18 interactions interaction NOUN cana-2813 8 19 through through ADP cana-2813 8 20 bidirectional bidirectional ADJ cana-2813 8 21 contextual contextual ADJ cana-2813 8 22 embeddings embedding NOUN cana-2813 8 23 . . PUNCT cana-2813 9 1 mfo mfo PROPN cana-2813 9 2 , , PUNCT cana-2813 9 3 a a DET cana-2813 9 4 bio bio ADJ cana-2813 9 5 - - PUNCT cana-2813 9 6 inspired inspired ADJ cana-2813 9 7 optimization optimization NOUN cana-2813 9 8 technique technique NOUN cana-2813 9 9 , , PUNCT cana-2813 9 10 addresses address NOUN cana-2813 9 11 feature feature VERB cana-2813 9 12 selection selection NOUN cana-2813 9 13 and and CCONJ cana-2813 9 14 hyperparameter hyperparameter NOUN cana-2813 9 15 tuning tune VERB cana-2813 9 16 by by ADP cana-2813 9 17 balancing balance VERB cana-2813 9 18 exploration exploration NOUN cana-2813 9 19 and and CCONJ cana-2813 9 20 exploitation exploitation NOUN cana-2813 9 21 in in ADP cana-2813 9 22 high high ADJ cana-2813 9 23 - - PUNCT cana-2813 9 24 dimensional dimensional ADJ cana-2813 9 25 search search NOUN cana-2813 9 26 spaces space NOUN cana-2813 9 27 . . PUNCT cana-2813 10 1 the the DET cana-2813 10 2 framework framework NOUN cana-2813 10 3 , , PUNCT cana-2813 10 4 dnabert dnabert NOUN cana-2813 10 5 - - PUNCT cana-2813 10 6 mfo mfo NOUN cana-2813 10 7 , , PUNCT cana-2813 10 8 leverages leverage VERB cana-2813 10 9 mfo mfo NOUN cana-2813 10 10 to to PART cana-2813 10 11 identify identify VERB cana-2813 10 12 the the DET cana-2813 10 13 most most ADV cana-2813 10 14 relevant relevant ADJ cana-2813 10 15 gene gene NOUN cana-2813 10 16 subsets subset NOUN cana-2813 10 17 and and CCONJ cana-2813 10 18 optimize optimize VERB cana-2813 10 19 dnabert dnabert NOUN cana-2813 10 20 's 's PART cana-2813 10 21 hyperparameters hyperparameter NOUN cana-2813 10 22 , , PUNCT cana-2813 10 23 improving improve VERB cana-2813 10 24 the the DET cana-2813 10 25 model model NOUN cana-2813 10 26 ’s ’s PART cana-2813 10 27 performance performance NOUN cana-2813 10 28 . . PUNCT cana-2813 11 1 evaluations evaluation NOUN cana-2813 11 2 conducted conduct VERB cana-2813 11 3 on on ADP cana-2813 11 4 multiple multiple ADJ cana-2813 11 5 microarray microarray NOUN cana-2813 11 6 datasets dataset NOUN cana-2813 11 7 , , PUNCT cana-2813 11 8 demonstrate demonstrate VERB cana-2813 11 9 that that SCONJ cana-2813 11 10 dnabert dnabert NOUN cana-2813 11 11 - - PUNCT cana-2813 11 12 mfo mfo NOUN cana-2813 11 13 with with ADP cana-2813 11 14 overall overall ADJ cana-2813 11 15 accuracy accuracy NOUN cana-2813 11 16 of of ADP cana-2813 11 17 above above ADP cana-2813 11 18 80 80 NUM cana-2813 11 19 % % NOUN cana-2813 11 20 significantly significantly ADV cana-2813 11 21 outperforms outperform VERB cana-2813 11 22 traditional traditional ADJ cana-2813 11 23 machine machine NOUN cana-2813 11 24 learning learn VERB cana-2813 11 25 methods method NOUN cana-2813 11 26 and and CCONJ cana-2813 11 27 standalone standalone ADJ cana-2813 11 28 deep deep ADJ cana-2813 11 29 learning learning NOUN cana-2813 11 30 models model NOUN cana-2813 11 31 in in ADP cana-2813 11 32 classification classification NOUN cana-2813 11 33 accuracy accuracy NOUN cana-2813 11 34 . . PUNCT cana-2813 12 1 this this DET cana-2813 12 2 integrated integrate VERB cana-2813 12 3 method method NOUN cana-2813 12 4 not not PART cana-2813 12 5 only only ADV cana-2813 12 6 enhances enhance VERB cana-2813 12 7 the the DET cana-2813 12 8 robustness robustness NOUN cana-2813 12 9 of of ADP cana-2813 12 10 gene gene NOUN cana-2813 12 11 expression expression NOUN cana-2813 12 12 data datum NOUN cana-2813 12 13 analysis analysis NOUN cana-2813 12 14 but but CCONJ cana-2813 12 15 also also ADV cana-2813 12 16 offers offer VERB cana-2813 12 17 a a DET cana-2813 12 18 powerful powerful ADJ cana-2813 12 19 tool tool NOUN cana-2813 12 20 for for ADP cana-2813 12 21 research research NOUN cana-2813 12 22 and and CCONJ cana-2813 12 23 clinical clinical ADJ cana-2813 12 24 applications application NOUN cana-2813 12 25 in in ADP cana-2813 12 26 genomics genomic NOUN cana-2813 12 27 . . PUNCT cana-2813 13 1 the the DET cana-2813 13 2 proposed propose VERB cana-2813 13 3 method method NOUN cana-2813 13 4 addresses address VERB cana-2813 13 5 key key ADJ cana-2813 13 6 limitations limitation NOUN cana-2813 13 7 of of ADP cana-2813 13 8 existing exist VERB cana-2813 13 9 techniques technique NOUN cana-2813 13 10 and and CCONJ cana-2813 13 11 provides provide VERB cana-2813 13 12 a a DET cana-2813 13 13 promising promising ADJ cana-2813 13 14 avenue avenue NOUN cana-2813 13 15 for for ADP cana-2813 13 16 future future ADJ cana-2813 13 17 advancements advancement NOUN cana-2813 13 18 in in ADP cana-2813 13 19 gene gene NOUN cana-2813 13 20 expression expression NOUN cana-2813 13 21 classification classification NOUN cana-2813 13 22 . . PUNCT cana-2813 14 1 keywords keyword NOUN cana-2813 14 2 : : PUNCT cana-2813 14 3 microarray microarray NOUN cana-2813 14 4 , , PUNCT cana-2813 14 5 gene gene NOUN cana-2813 14 6 expression expression NOUN cana-2813 14 7 classification classification NOUN cana-2813 14 8 , , PUNCT cana-2813 14 9 mayfly mayfly NOUN cana-2813 14 10 optimization optimization NOUN cana-2813 14 11 algorithm algorithm NOUN cana-2813 14 12 . . PUNCT cana-2813 15 1 1 1 X cana-2813 15 2 . . X cana-2813 15 3 introduction introduction NOUN cana-2813 15 4 microarray microarray NOUN cana-2813 15 5 gene gene NOUN cana-2813 15 6 expression expression NOUN cana-2813 15 7 data datum NOUN cana-2813 15 8 analysis analysis NOUN cana-2813 15 9 has have AUX cana-2813 15 10 profoundly profoundly ADV cana-2813 15 11 impacted impact VERB cana-2813 15 12 genomics genomic NOUN cana-2813 15 13 and and CCONJ cana-2813 15 14 biomedical biomedical ADJ cana-2813 15 15 research research NOUN cana-2813 15 16 by by ADP cana-2813 15 17 offering offer VERB cana-2813 15 18 detailed detailed ADJ cana-2813 15 19 insights insight NOUN cana-2813 15 20 into into ADP cana-2813 15 21 the the DET cana-2813 15 22 genetic genetic ADJ cana-2813 15 23 basis basis NOUN cana-2813 15 24 of of ADP cana-2813 15 25 many many ADJ cana-2813 15 26 diseases disease NOUN cana-2813 15 27 , , PUNCT cana-2813 15 28 including include VERB cana-2813 15 29 cancer cancer NOUN cana-2813 15 30 , , PUNCT cana-2813 15 31 cardiovascular cardiovascular ADJ cana-2813 15 32 diseases disease NOUN cana-2813 15 33 , , PUNCT cana-2813 15 34 and and CCONJ cana-2813 15 35 neurodegenerative neurodegenerative ADJ cana-2813 15 36 disorders disorder NOUN cana-2813 15 37 . . PUNCT cana-2813 16 1 microarray microarray PROPN cana-2813 16 2 technology technology PROPN cana-2813 16 3 aids aid VERB cana-2813 16 4 the the DET cana-2813 16 5 concurrent concurrent ADJ cana-2813 16 6 measurement measurement NOUN cana-2813 16 7 of of ADP cana-2813 16 8 expression expression NOUN cana-2813 16 9 levels level NOUN cana-2813 16 10 for for ADP cana-2813 16 11 thousands thousand NOUN cana-2813 16 12 of of ADP cana-2813 16 13 genes gene NOUN cana-2813 16 14 across across ADP cana-2813 16 15 different different ADJ cana-2813 16 16 conditions condition NOUN cana-2813 16 17 , , PUNCT cana-2813 16 18 providing provide VERB cana-2813 16 19 a a DET cana-2813 16 20 comprehensive comprehensive ADJ cana-2813 16 21 overview overview NOUN cana-2813 16 22 of of ADP cana-2813 16 23 cellular cellular ADJ cana-2813 16 24 states state NOUN cana-2813 16 25 [ [ X cana-2813 16 26 1 1 NUM cana-2813 16 27 ] ] PUNCT cana-2813 16 28 . . PUNCT cana-2813 17 1 this this DET cana-2813 17 2 capability capability NOUN cana-2813 17 3 is be AUX cana-2813 17 4 critical critical ADJ cana-2813 17 5 for for ADP cana-2813 17 6 deciphering decipher VERB cana-2813 17 7 the the DET cana-2813 17 8 mailto:shyamalagowribalaraman@gmail.com mailto:shyamalagowribalaraman@gmail.com PROPN cana-2813 17 9 mailto:anu_jul@yahoo.co.in mailto:anu_jul@yahoo.co.in PART cana-2813 17 10 mailto:sanalprabha@yahoo.co.in mailto:sanalprabha@yahoo.co.in PROPN cana-2813 17 11 communications communication NOUN cana-2813 17 12 on on ADP cana-2813 17 13 applied apply VERB cana-2813 17 14 nonlinear nonlinear ADJ cana-2813 17 15 analysis analysis NOUN cana-2813 17 16 issn issn NOUN cana-2813 17 17 : : PUNCT cana-2813 17 18 1074 1074 NUM cana-2813 17 19 - - PUNCT cana-2813 17 20 133x 133x NUM cana-2813 17 21 vol vol NOUN cana-2813 17 22 32 32 NUM cana-2813 17 23 no no NOUN cana-2813 17 24 . . PUNCT cana-2813 18 1 4s 4s NUM cana-2813 18 2 ( ( PUNCT cana-2813 18 3 2025 2025 NUM cana-2813 18 4 ) ) PUNCT cana-2813 18 5 271 271 NUM cana-2813 18 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 18 7 molecular molecular ADJ cana-2813 18 8 mechanisms mechanism NOUN cana-2813 18 9 underlying underlie VERB cana-2813 18 10 diseases disease NOUN cana-2813 18 11 , , PUNCT cana-2813 18 12 discovering discover VERB cana-2813 18 13 potential potential ADJ cana-2813 18 14 biomarkers biomarker NOUN cana-2813 18 15 for for ADP cana-2813 18 16 early early ADJ cana-2813 18 17 diagnosis diagnosis NOUN cana-2813 18 18 , , PUNCT cana-2813 18 19 and and CCONJ cana-2813 18 20 developing develop VERB cana-2813 18 21 targeted target VERB cana-2813 18 22 therapeutic therapeutic ADJ cana-2813 18 23 strategies strategy NOUN cana-2813 18 24 [ [ X cana-2813 18 25 2 2 NUM cana-2813 18 26 ] ] PUNCT cana-2813 18 27 . . PUNCT cana-2813 19 1 however however ADV cana-2813 19 2 , , PUNCT cana-2813 19 3 despite despite SCONJ cana-2813 19 4 its its PRON cana-2813 19 5 potential potential NOUN cana-2813 19 6 , , PUNCT cana-2813 19 7 the the DET cana-2813 19 8 analysis analysis NOUN cana-2813 19 9 of of ADP cana-2813 19 10 microarray microarray NOUN cana-2813 19 11 data datum NOUN cana-2813 19 12 is be AUX cana-2813 19 13 fraught fraught ADJ cana-2813 19 14 with with ADP cana-2813 19 15 challenges challenge NOUN cana-2813 19 16 primarily primarily ADV cana-2813 19 17 due due ADP cana-2813 19 18 to to ADP cana-2813 19 19 the the DET cana-2813 19 20 high high ADJ cana-2813 19 21 dimensionality dimensionality NOUN cana-2813 19 22 of of ADP cana-2813 19 23 the the DET cana-2813 19 24 data datum NOUN cana-2813 19 25 . . PUNCT cana-2813 20 1 in in ADP cana-2813 20 2 these these DET cana-2813 20 3 datasets dataset NOUN cana-2813 20 4 , , PUNCT cana-2813 20 5 the the DET cana-2813 20 6 number number NOUN cana-2813 20 7 of of ADP cana-2813 20 8 genes gene NOUN cana-2813 20 9 ( ( PUNCT cana-2813 20 10 features feature NOUN cana-2813 20 11 ) ) PUNCT cana-2813 20 12 often often ADV cana-2813 20 13 far far ADV cana-2813 20 14 exceeds exceed VERB cana-2813 20 15 the the DET cana-2813 20 16 number number NOUN cana-2813 20 17 of of ADP cana-2813 20 18 available available ADJ cana-2813 20 19 samples sample NOUN cana-2813 20 20 ( ( PUNCT cana-2813 20 21 instances instance NOUN cana-2813 20 22 ) ) PUNCT cana-2813 20 23 , , PUNCT cana-2813 20 24 creating create VERB cana-2813 20 25 what what PRON cana-2813 20 26 is be AUX cana-2813 20 27 known know VERB cana-2813 20 28 as as ADP cana-2813 20 29 the the DET cana-2813 20 30 " " PUNCT cana-2813 20 31 curse curse NOUN cana-2813 20 32 of of ADP cana-2813 20 33 dimensionality dimensionality NOUN cana-2813 20 34 " " PUNCT cana-2813 21 1 [ [ X cana-2813 21 2 3 3 NUM cana-2813 21 3 ] ] PUNCT cana-2813 21 4 . . PUNCT cana-2813 22 1 this this DET cana-2813 22 2 imbalance imbalance NOUN cana-2813 22 3 complicates complicate VERB cana-2813 22 4 the the DET cana-2813 22 5 task task NOUN cana-2813 22 6 of of ADP cana-2813 22 7 identifying identify VERB cana-2813 22 8 the the DET cana-2813 22 9 most most ADV cana-2813 22 10 relevant relevant ADJ cana-2813 22 11 genes gene NOUN cana-2813 22 12 for for ADP cana-2813 22 13 disease disease NOUN cana-2813 22 14 classification classification NOUN cana-2813 22 15 , , PUNCT cana-2813 22 16 leading lead VERB cana-2813 22 17 to to ADP cana-2813 22 18 potential potential ADJ cana-2813 22 19 overfitting overfitting NOUN cana-2813 22 20 where where SCONJ cana-2813 22 21 models model NOUN cana-2813 22 22 perform perform VERB cana-2813 22 23 well well ADV cana-2813 22 24 on on ADP cana-2813 22 25 training training NOUN cana-2813 22 26 data datum NOUN cana-2813 22 27 but but CCONJ cana-2813 22 28 fail fail VERB cana-2813 22 29 to to PART cana-2813 22 30 take take VERB cana-2813 22 31 a a DET cana-2813 22 32 broad broad ADJ cana-2813 22 33 view view NOUN cana-2813 22 34 to to ADP cana-2813 22 35 new new ADJ cana-2813 22 36 data datum NOUN cana-2813 22 37 [ [ X cana-2813 22 38 4 4 NUM cana-2813 22 39 ] ] PUNCT cana-2813 22 40 . . PUNCT cana-2813 23 1 the the DET cana-2813 23 2 accurate accurate ADJ cana-2813 23 3 classification classification NOUN cana-2813 23 4 of of ADP cana-2813 23 5 diseases disease NOUN cana-2813 23 6 based base VERB cana-2813 23 7 on on ADP cana-2813 23 8 gene gene NOUN cana-2813 23 9 expression expression NOUN cana-2813 23 10 data datum NOUN cana-2813 23 11 has have VERB cana-2813 23 12 significant significant ADJ cana-2813 23 13 implications implication NOUN cana-2813 23 14 for for ADP cana-2813 23 15 clinical clinical ADJ cana-2813 23 16 practice practice NOUN cana-2813 23 17 . . PUNCT cana-2813 24 1 early early ADJ cana-2813 24 2 and and CCONJ cana-2813 24 3 precise precise ADJ cana-2813 24 4 diagnosis diagnosis NOUN cana-2813 24 5 can can AUX cana-2813 24 6 substantially substantially ADV cana-2813 24 7 enhance enhance VERB cana-2813 24 8 patient patient ADJ cana-2813 24 9 outcomes outcome NOUN cana-2813 24 10 through through ADP cana-2813 24 11 timely timely ADJ cana-2813 24 12 interventions intervention NOUN cana-2813 24 13 and and CCONJ cana-2813 24 14 personalized personalized ADJ cana-2813 24 15 treatment treatment NOUN cana-2813 24 16 plans plan NOUN cana-2813 24 17 . . PUNCT cana-2813 25 1 for for ADP cana-2813 25 2 instance instance NOUN cana-2813 25 3 , , PUNCT cana-2813 25 4 in in ADP cana-2813 25 5 oncology oncology NOUN cana-2813 25 6 , , PUNCT cana-2813 25 7 the the DET cana-2813 25 8 ability ability NOUN cana-2813 25 9 to to PART cana-2813 25 10 categorize categorize VERB cana-2813 25 11 tumors tumor NOUN cana-2813 25 12 into into ADP cana-2813 25 13 distinct distinct ADJ cana-2813 25 14 molecular molecular ADJ cana-2813 25 15 subtypes subtype NOUN cana-2813 25 16 facilitates facilitate VERB cana-2813 25 17 the the DET cana-2813 25 18 selection selection NOUN cana-2813 25 19 of of ADP cana-2813 25 20 targeted target VERB cana-2813 25 21 therapies therapy NOUN cana-2813 25 22 , , PUNCT cana-2813 25 23 thus thus ADV cana-2813 25 24 improving improve VERB cana-2813 25 25 treatment treatment NOUN cana-2813 25 26 efficacy efficacy NOUN cana-2813 25 27 while while SCONJ cana-2813 25 28 minimizing minimize VERB cana-2813 25 29 adverse adverse ADJ cana-2813 25 30 effects effect NOUN cana-2813 25 31 [ [ X cana-2813 25 32 5 5 NUM cana-2813 25 33 ] ] PUNCT cana-2813 25 34 . . PUNCT cana-2813 26 1 but but CCONJ cana-2813 26 2 , , PUNCT cana-2813 26 3 the the DET cana-2813 26 4 complication complication NOUN cana-2813 26 5 and and CCONJ cana-2813 26 6 heterogeneity heterogeneity NOUN cana-2813 26 7 of of ADP cana-2813 26 8 gene gene NOUN cana-2813 26 9 expression expression NOUN cana-2813 26 10 data datum NOUN cana-2813 26 11 , , PUNCT cana-2813 26 12 coupled couple VERB cana-2813 26 13 with with ADP cana-2813 26 14 the the DET cana-2813 26 15 limitations limitation NOUN cana-2813 26 16 of of ADP cana-2813 26 17 existing exist VERB cana-2813 26 18 analytical analytical ADJ cana-2813 26 19 techniques technique NOUN cana-2813 26 20 , , PUNCT cana-2813 26 21 highlight highlight VERB cana-2813 26 22 the the DET cana-2813 26 23 need need NOUN cana-2813 26 24 for for ADP cana-2813 26 25 more more ADV cana-2813 26 26 advanced advanced ADJ cana-2813 26 27 tools tool NOUN cana-2813 26 28 . . PUNCT cana-2813 27 1 recent recent ADJ cana-2813 27 2 developments development NOUN cana-2813 27 3 in in ADP cana-2813 27 4 machine machine NOUN cana-2813 27 5 learning learning NOUN cana-2813 27 6 ( ( PUNCT cana-2813 27 7 ml ml NOUN cana-2813 27 8 ) ) PUNCT cana-2813 27 9 and and CCONJ cana-2813 27 10 deep deep ADJ cana-2813 27 11 learning learning NOUN cana-2813 27 12 ( ( PUNCT cana-2813 27 13 dl dl INTJ cana-2813 27 14 ) ) PUNCT cana-2813 27 15 have have AUX cana-2813 27 16 introduced introduce VERB cana-2813 27 17 new new ADJ cana-2813 27 18 potentials potential NOUN cana-2813 27 19 for for ADP cana-2813 27 20 addressing address VERB cana-2813 27 21 the the DET cana-2813 27 22 challenges challenge NOUN cana-2813 27 23 associated associate VERB cana-2813 27 24 with with ADP cana-2813 27 25 high high ADJ cana-2813 27 26 - - PUNCT cana-2813 27 27 dimensional dimensional ADJ cana-2813 27 28 data datum NOUN cana-2813 27 29 . . PUNCT cana-2813 28 1 traditional traditional ADJ cana-2813 28 2 methods method NOUN cana-2813 28 3 such such ADJ cana-2813 28 4 as as ADP cana-2813 28 5 support support NOUN cana-2813 28 6 vector vector NOUN cana-2813 28 7 machines machine NOUN cana-2813 28 8 ( ( PUNCT cana-2813 28 9 svms svms NOUN cana-2813 28 10 ) ) PUNCT cana-2813 29 1 [ [ X cana-2813 29 2 6 6 NUM cana-2813 29 3 ] ] PUNCT cana-2813 29 4 and and CCONJ cana-2813 29 5 random random ADJ cana-2813 29 6 forests forest NOUN cana-2813 29 7 [ [ X cana-2813 29 8 7 7 X cana-2813 29 9 ] ] PUNCT cana-2813 29 10 have have AUX cana-2813 29 11 demonstrated demonstrate VERB cana-2813 29 12 some some DET cana-2813 29 13 success success NOUN cana-2813 29 14 , , PUNCT cana-2813 29 15 but but CCONJ cana-2813 29 16 they they PRON cana-2813 29 17 often often ADV cana-2813 29 18 fall fall VERB cana-2813 29 19 short short ADJ cana-2813 29 20 in in ADP cana-2813 29 21 capturing capture VERB cana-2813 29 22 the the DET cana-2813 29 23 intricate intricate ADJ cana-2813 29 24 relationships relationship NOUN cana-2813 29 25 within within ADP cana-2813 29 26 high high ADJ cana-2813 29 27 - - PUNCT cana-2813 29 28 dimensional dimensional ADJ cana-2813 29 29 genomic genomic ADJ cana-2813 29 30 data datum NOUN cana-2813 29 31 . . PUNCT cana-2813 30 1 these these DET cana-2813 30 2 methods method NOUN cana-2813 30 3 , , PUNCT cana-2813 30 4 while while SCONJ cana-2813 30 5 beneficial beneficial ADJ cana-2813 30 6 , , PUNCT cana-2813 30 7 encounter encounter ADJ cana-2813 30 8 limitations limitation NOUN cana-2813 30 9 in in ADP cana-2813 30 10 gene gene NOUN cana-2813 30 11 selection selection NOUN cana-2813 30 12 and and CCONJ cana-2813 30 13 model model NOUN cana-2813 30 14 parameter parameter PROPN cana-2813 30 15 tuning tuning NOUN cana-2813 30 16 , , PUNCT cana-2813 30 17 which which PRON cana-2813 30 18 can can AUX cana-2813 30 19 impact impact VERB cana-2813 30 20 their their PRON cana-2813 30 21 overall overall ADJ cana-2813 30 22 performance performance NOUN cana-2813 30 23 . . PUNCT cana-2813 31 1 over over ADP cana-2813 31 2 the the DET cana-2813 31 3 past past ADJ cana-2813 31 4 two two NUM cana-2813 31 5 decades decade NOUN cana-2813 31 6 , , PUNCT cana-2813 31 7 researchers researcher NOUN cana-2813 31 8 have have AUX cana-2813 31 9 explored explore VERB cana-2813 31 10 various various ADJ cana-2813 31 11 ml ml NOUN cana-2813 31 12 and and CCONJ cana-2813 31 13 statistical statistical ADJ cana-2813 31 14 techniques technique NOUN cana-2813 31 15 for for ADP cana-2813 31 16 microarray microarray NOUN cana-2813 31 17 data datum NOUN cana-2813 31 18 classification classification NOUN cana-2813 31 19 . . PUNCT cana-2813 32 1 early early ADJ cana-2813 32 2 approaches approach NOUN cana-2813 32 3 relied rely VERB cana-2813 32 4 on on ADP cana-2813 32 5 traditional traditional ADJ cana-2813 32 6 methods method NOUN cana-2813 32 7 like like ADP cana-2813 32 8 linear linear ADJ cana-2813 32 9 discriminant discriminant ADJ cana-2813 32 10 analysis analysis NOUN cana-2813 32 11 ( ( PUNCT cana-2813 32 12 lda lda PROPN cana-2813 32 13 ) ) PUNCT cana-2813 32 14 and and CCONJ cana-2813 32 15 principal principal ADJ cana-2813 32 16 component component NOUN cana-2813 32 17 analysis analysis NOUN cana-2813 32 18 ( ( PUNCT cana-2813 32 19 pca pca NOUN cana-2813 32 20 ) ) PUNCT cana-2813 32 21 , , PUNCT cana-2813 32 22 which which PRON cana-2813 32 23 aimed aim VERB cana-2813 32 24 to to PART cana-2813 32 25 reduce reduce VERB cana-2813 32 26 dimensionality dimensionality NOUN cana-2813 32 27 and and CCONJ cana-2813 32 28 identify identify VERB cana-2813 32 29 significant significant ADJ cana-2813 32 30 gene gene NOUN cana-2813 32 31 subsets subset NOUN cana-2813 32 32 . . PUNCT cana-2813 33 1 although although SCONJ cana-2813 33 2 these these DET cana-2813 33 3 methods method NOUN cana-2813 33 4 laid lay VERB cana-2813 33 5 the the DET cana-2813 33 6 groundwork groundwork NOUN cana-2813 33 7 , , PUNCT cana-2813 33 8 they they PRON cana-2813 33 9 struggled struggle VERB cana-2813 33 10 with with ADP cana-2813 33 11 the the DET cana-2813 33 12 complexity complexity NOUN cana-2813 33 13 and and CCONJ cana-2813 33 14 high high ADJ cana-2813 33 15 dimensionality dimensionality NOUN cana-2813 33 16 of of ADP cana-2813 33 17 microarray microarray NOUN cana-2813 33 18 data datum NOUN cana-2813 33 19 [ [ X cana-2813 33 20 8 8 NUM cana-2813 33 21 ] ] PUNCT cana-2813 33 22 . . PUNCT cana-2813 34 1 the the DET cana-2813 34 2 advent advent NOUN cana-2813 34 3 of of ADP cana-2813 34 4 machine machine NOUN cana-2813 34 5 learning learning NOUN cana-2813 34 6 brought bring VERB cana-2813 34 7 more more ADV cana-2813 34 8 sophisticated sophisticated ADJ cana-2813 34 9 techniques technique NOUN cana-2813 34 10 such such ADJ cana-2813 34 11 as as ADP cana-2813 34 12 svms svms NOUN cana-2813 34 13 , , PUNCT cana-2813 34 14 k k ADJ cana-2813 34 15 - - PUNCT cana-2813 34 16 nearest near ADJ cana-2813 34 17 neighbors neighbor NOUN cana-2813 34 18 ( ( PUNCT cana-2813 34 19 k k X cana-2813 34 20 - - PUNCT cana-2813 34 21 nn nn NOUN cana-2813 34 22 ) ) PUNCT cana-2813 35 1 [ [ X cana-2813 35 2 9 9 NUM cana-2813 35 3 ] ] PUNCT cana-2813 35 4 , , PUNCT cana-2813 35 5 and and CCONJ cana-2813 35 6 random random ADJ cana-2813 35 7 forests forest NOUN cana-2813 35 8 [ [ X cana-2813 35 9 10 10 NUM cana-2813 35 10 ] ] PUNCT cana-2813 35 11 , , PUNCT cana-2813 35 12 which which PRON cana-2813 35 13 improved improve VERB cana-2813 35 14 classification classification NOUN cana-2813 35 15 accuracy accuracy NOUN cana-2813 35 16 and and CCONJ cana-2813 35 17 handling handling NOUN cana-2813 35 18 of of ADP cana-2813 35 19 high high ADJ cana-2813 35 20 - - PUNCT cana-2813 35 21 dimensional dimensional ADJ cana-2813 35 22 data datum NOUN cana-2813 35 23 . . PUNCT cana-2813 36 1 despite despite SCONJ cana-2813 36 2 their their PRON cana-2813 36 3 advancements advancement NOUN cana-2813 36 4 , , PUNCT cana-2813 36 5 these these DET cana-2813 36 6 methods method NOUN cana-2813 36 7 have have VERB cana-2813 36 8 limitations limitation NOUN cana-2813 36 9 . . PUNCT cana-2813 37 1 for for ADP cana-2813 37 2 example example NOUN cana-2813 37 3 , , PUNCT cana-2813 37 4 svms svms NOUN cana-2813 37 5 require require VERB cana-2813 37 6 careful careful ADJ cana-2813 37 7 selection selection NOUN cana-2813 37 8 of of ADP cana-2813 37 9 kernel kernel NOUN cana-2813 37 10 functions function NOUN cana-2813 37 11 and and CCONJ cana-2813 37 12 hyperparameter hyperparameter NOUN cana-2813 37 13 tuning tuning NOUN cana-2813 37 14 , , PUNCT cana-2813 37 15 while while SCONJ cana-2813 37 16 random random ADJ cana-2813 37 17 forests forest NOUN cana-2813 37 18 , , PUNCT cana-2813 37 19 although although SCONJ cana-2813 37 20 robust robust ADJ cana-2813 37 21 , , PUNCT cana-2813 37 22 often often ADV cana-2813 37 23 produce produce VERB cana-2813 37 24 models model NOUN cana-2813 37 25 that that PRON cana-2813 37 26 are be AUX cana-2813 37 27 difficult difficult ADJ cana-2813 37 28 to to PART cana-2813 37 29 interpret interpret VERB cana-2813 37 30 [ [ PRON cana-2813 37 31 11 11 NUM cana-2813 37 32 ] ] PUNCT cana-2813 37 33 . . PUNCT cana-2813 38 1 the the DET cana-2813 38 2 exploration exploration NOUN cana-2813 38 3 of of ADP cana-2813 38 4 deep deep ADJ cana-2813 38 5 learning learning NOUN cana-2813 38 6 models model NOUN cana-2813 38 7 , , PUNCT cana-2813 38 8 particularly particularly ADV cana-2813 38 9 convolutional convolutional ADJ cana-2813 38 10 neural neural ADJ cana-2813 38 11 networks network NOUN cana-2813 38 12 ( ( PUNCT cana-2813 38 13 cnns cnns PROPN cana-2813 38 14 ) ) PUNCT cana-2813 38 15 and and CCONJ cana-2813 38 16 recurrent recurrent ADJ cana-2813 38 17 neural neural ADJ cana-2813 38 18 networks network NOUN cana-2813 38 19 ( ( PUNCT cana-2813 38 20 rnns rnns PROPN cana-2813 38 21 ) ) PUNCT cana-2813 39 1 [ [ X cana-2813 39 2 12 12 NUM cana-2813 39 3 , , PUNCT cana-2813 39 4 13 13 NUM cana-2813 39 5 ] ] PUNCT cana-2813 39 6 , , PUNCT cana-2813 39 7 has have AUX cana-2813 39 8 further far ADV cana-2813 39 9 advanced advance VERB cana-2813 39 10 the the DET cana-2813 39 11 field field NOUN cana-2813 39 12 by by ADP cana-2813 39 13 learning learn VERB cana-2813 39 14 hierarchical hierarchical ADJ cana-2813 39 15 data datum NOUN cana-2813 39 16 representations representation NOUN cana-2813 39 17 . . PUNCT cana-2813 40 1 however however ADV cana-2813 40 2 , , PUNCT cana-2813 40 3 their their PRON cana-2813 40 4 application application NOUN cana-2813 40 5 to to ADP cana-2813 40 6 microarray microarray NOUN cana-2813 40 7 data datum NOUN cana-2813 40 8 is be AUX cana-2813 40 9 constrained constrain VERB cana-2813 40 10 by by ADP cana-2813 40 11 the the DET cana-2813 40 12 need need NOUN cana-2813 40 13 for for ADP cana-2813 40 14 large large ADJ cana-2813 40 15 training training NOUN cana-2813 40 16 datasets dataset NOUN cana-2813 40 17 , , PUNCT cana-2813 40 18 which which PRON cana-2813 40 19 are be AUX cana-2813 40 20 often often ADV cana-2813 40 21 not not PART cana-2813 40 22 available available ADJ cana-2813 40 23 in in ADP cana-2813 40 24 the the DET cana-2813 40 25 biomedical biomedical ADJ cana-2813 40 26 domain domain NOUN cana-2813 40 27 [ [ X cana-2813 40 28 14 14 NUM cana-2813 40 29 ] ] PUNCT cana-2813 40 30 . . PUNCT cana-2813 41 1 this this DET cana-2813 41 2 challenge challenge NOUN cana-2813 41 3 has have AUX cana-2813 41 4 led lead VERB cana-2813 41 5 to to ADP cana-2813 41 6 the the DET cana-2813 41 7 adoption adoption NOUN cana-2813 41 8 of of ADP cana-2813 41 9 transfer transfer NOUN cana-2813 41 10 learning learning NOUN cana-2813 41 11 methods method NOUN cana-2813 41 12 , , PUNCT cana-2813 41 13 where where SCONJ cana-2813 41 14 models model NOUN cana-2813 41 15 pre pre VERB cana-2813 41 16 - - VERB cana-2813 41 17 trained train VERB cana-2813 41 18 on on ADP cana-2813 41 19 extensive extensive ADJ cana-2813 41 20 datasets dataset NOUN cana-2813 41 21 are be AUX cana-2813 41 22 fine fine ADV cana-2813 41 23 - - PUNCT cana-2813 41 24 tuned tune VERB cana-2813 41 25 on on ADP cana-2813 41 26 lesser less ADJ cana-2813 41 27 , , PUNCT cana-2813 41 28 domain domain NOUN cana-2813 41 29 - - PUNCT cana-2813 41 30 specific specific ADJ cana-2813 41 31 datasets dataset NOUN cana-2813 41 32 [ [ X cana-2813 41 33 15 15 NUM cana-2813 41 34 ] ] PUNCT cana-2813 41 35 . . PUNCT cana-2813 42 1 deep deep ADJ cana-2813 42 2 learning learning NOUN cana-2813 42 3 models model NOUN cana-2813 42 4 , , PUNCT cana-2813 42 5 including include VERB cana-2813 42 6 cnns cnn NOUN cana-2813 42 7 and and CCONJ cana-2813 42 8 rnns rnn NOUN cana-2813 42 9 , , PUNCT cana-2813 42 10 have have AUX cana-2813 42 11 shown show VERB cana-2813 42 12 promise promise NOUN cana-2813 42 13 in in ADP cana-2813 42 14 automatically automatically ADV cana-2813 42 15 learning learn VERB cana-2813 42 16 data data NOUN cana-2813 42 17 representations representation NOUN cana-2813 42 18 , , PUNCT cana-2813 42 19 reducing reduce VERB cana-2813 42 20 the the DET cana-2813 42 21 necessity necessity NOUN cana-2813 42 22 for for ADP cana-2813 42 23 manual manual ADJ cana-2813 42 24 feature feature NOUN cana-2813 42 25 selection selection NOUN cana-2813 42 26 . . PUNCT cana-2813 43 1 the the DET cana-2813 43 2 introduction introduction NOUN cana-2813 43 3 of of ADP cana-2813 43 4 transfer transfer NOUN cana-2813 43 5 learning learning NOUN cana-2813 43 6 techniques technique NOUN cana-2813 43 7 has have AUX cana-2813 43 8 further far ADV cana-2813 43 9 enhanced enhance VERB cana-2813 43 10 these these DET cana-2813 43 11 models model NOUN cana-2813 43 12 ' ' PART cana-2813 43 13 applicability applicability NOUN cana-2813 43 14 to to PART cana-2813 43 15 microarray microarray VERB cana-2813 43 16 data data PROPN cana-2813 43 17 . . PUNCT cana-2813 44 1 dnabert dnabert PROPN cana-2813 44 2 , , PUNCT cana-2813 44 3 a a DET cana-2813 44 4 transformer transformer NOUN cana-2813 44 5 - - PUNCT cana-2813 44 6 based base VERB cana-2813 44 7 model model NOUN cana-2813 44 8 pre pre VERB cana-2813 44 9 - - VERB cana-2813 44 10 trained train VERB cana-2813 44 11 on on ADP cana-2813 44 12 genomic genomic ADJ cana-2813 44 13 sequences sequence NOUN cana-2813 44 14 , , PUNCT cana-2813 44 15 exemplifies exemplify VERB cana-2813 44 16 this this DET cana-2813 44 17 approach approach NOUN cana-2813 44 18 . . PUNCT cana-2813 45 1 by by ADP cana-2813 45 2 leveraging leverage VERB cana-2813 45 3 its its PRON cana-2813 45 4 pretraining pretraine VERB cana-2813 45 5 on on ADP cana-2813 45 6 extensive extensive ADJ cana-2813 45 7 genomic genomic NOUN cana-2813 45 8 communications communication NOUN cana-2813 45 9 on on ADP cana-2813 45 10 applied apply VERB cana-2813 45 11 nonlinear nonlinear ADJ cana-2813 45 12 analysis analysis NOUN cana-2813 45 13 issn issn NOUN cana-2813 45 14 : : PUNCT cana-2813 45 15 1074 1074 NUM cana-2813 45 16 - - PUNCT cana-2813 45 17 133x 133x NUM cana-2813 45 18 vol vol NOUN cana-2813 45 19 32 32 NUM cana-2813 45 20 no no NOUN cana-2813 45 21 . . PUNCT cana-2813 46 1 4s 4s NUM cana-2813 46 2 ( ( PUNCT cana-2813 46 3 2025 2025 NUM cana-2813 46 4 ) ) PUNCT cana-2813 46 5 272 272 NUM cana-2813 46 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 46 7 data datum NOUN cana-2813 46 8 , , PUNCT cana-2813 46 9 dnabert dnabert PROPN cana-2813 46 10 captures capture NOUN cana-2813 46 11 contextual contextual ADJ cana-2813 46 12 relationships relationship NOUN cana-2813 46 13 between between ADP cana-2813 46 14 genes gene NOUN cana-2813 46 15 , , PUNCT cana-2813 46 16 making make VERB cana-2813 46 17 it it PRON cana-2813 46 18 well well ADV cana-2813 46 19 - - PUNCT cana-2813 46 20 suited suit VERB cana-2813 46 21 for for ADP cana-2813 46 22 gene gene NOUN cana-2813 46 23 expression expression NOUN cana-2813 46 24 classification classification NOUN cana-2813 47 1 [ [ X cana-2813 47 2 16 16 NUM cana-2813 47 3 ] ] PUNCT cana-2813 47 4 . . PUNCT cana-2813 48 1 despite despite SCONJ cana-2813 48 2 these these DET cana-2813 48 3 advancements advancement NOUN cana-2813 48 4 , , PUNCT cana-2813 48 5 there there PRON cana-2813 48 6 remains remain VERB cana-2813 48 7 a a DET cana-2813 48 8 need need NOUN cana-2813 48 9 for for ADP cana-2813 48 10 effective effective ADJ cana-2813 48 11 optimization optimization NOUN cana-2813 48 12 methods method NOUN cana-2813 48 13 to to PART cana-2813 48 14 enhance enhance VERB cana-2813 48 15 the the DET cana-2813 48 16 performance performance NOUN cana-2813 48 17 of of ADP cana-2813 48 18 deep deep ADJ cana-2813 48 19 learning learning NOUN cana-2813 48 20 models model NOUN cana-2813 48 21 . . PUNCT cana-2813 49 1 the the DET cana-2813 49 2 mayfly mayfly NOUN cana-2813 49 3 optimization optimization NOUN cana-2813 49 4 algorithm algorithm NOUN cana-2813 49 5 ( ( PUNCT cana-2813 49 6 mfo mfo PROPN cana-2813 49 7 ) ) PUNCT cana-2813 49 8 , , PUNCT cana-2813 49 9 inspired inspire VERB cana-2813 49 10 by by ADP cana-2813 49 11 the the DET cana-2813 49 12 swarming swarm VERB cana-2813 49 13 behavior behavior NOUN cana-2813 49 14 of of ADP cana-2813 49 15 mayflies mayfly NOUN cana-2813 49 16 during during ADP cana-2813 49 17 mating mating NOUN cana-2813 49 18 , , PUNCT cana-2813 49 19 offers offer VERB cana-2813 49 20 a a DET cana-2813 49 21 novel novel ADJ cana-2813 49 22 solution solution NOUN cana-2813 49 23 . . PUNCT cana-2813 50 1 mfo mfo PROPN cana-2813 50 2 has have AUX cana-2813 50 3 proven prove VERB cana-2813 50 4 effective effective ADJ cana-2813 50 5 in in ADP cana-2813 50 6 various various ADJ cana-2813 50 7 optimization optimization NOUN cana-2813 50 8 tasks task NOUN cana-2813 50 9 across across ADP cana-2813 50 10 different different ADJ cana-2813 50 11 domains domain NOUN cana-2813 50 12 , , PUNCT cana-2813 50 13 but but CCONJ cana-2813 50 14 its its PRON cana-2813 50 15 application application NOUN cana-2813 50 16 to to PART cana-2813 50 17 microarray microarray VERB cana-2813 50 18 gene gene NOUN cana-2813 50 19 expression expression NOUN cana-2813 50 20 data datum NOUN cana-2813 50 21 analysis analysis NOUN cana-2813 50 22 is be AUX cana-2813 50 23 relatively relatively ADV cana-2813 50 24 unexplored unexplored ADJ cana-2813 50 25 [ [ PUNCT cana-2813 50 26 17 17 NUM cana-2813 50 27 ] ] PUNCT cana-2813 50 28 . . PUNCT cana-2813 51 1 mfo mfo PROPN cana-2813 51 2 provides provide VERB cana-2813 51 3 a a DET cana-2813 51 4 unique unique ADJ cana-2813 51 5 balance balance NOUN cana-2813 51 6 between between ADP cana-2813 51 7 exploration exploration NOUN cana-2813 51 8 and and CCONJ cana-2813 51 9 exploitation exploitation NOUN cana-2813 51 10 , , PUNCT cana-2813 51 11 making make VERB cana-2813 51 12 it it PRON cana-2813 51 13 a a DET cana-2813 51 14 promising promising ADJ cana-2813 51 15 tool tool NOUN cana-2813 51 16 for for ADP cana-2813 51 17 optimizing optimize VERB cana-2813 51 18 gene gene NOUN cana-2813 51 19 subset subset NOUN cana-2813 51 20 selection selection NOUN cana-2813 51 21 and and CCONJ cana-2813 51 22 model model NOUN cana-2813 51 23 parameters parameter NOUN cana-2813 51 24 . . PUNCT cana-2813 52 1 in in ADP cana-2813 52 2 parallel parallel NOUN cana-2813 52 3 , , PUNCT cana-2813 52 4 other other ADJ cana-2813 52 5 optimization optimization NOUN cana-2813 52 6 algorithms algorithm NOUN cana-2813 52 7 such such ADJ cana-2813 52 8 as as ADP cana-2813 52 9 genetic genetic ADJ cana-2813 52 10 algorithms algorithm NOUN cana-2813 52 11 ( ( PUNCT cana-2813 52 12 gas gas NOUN cana-2813 52 13 ) ) PUNCT cana-2813 53 1 [ [ X cana-2813 53 2 18 18 NUM cana-2813 53 3 ] ] PUNCT cana-2813 53 4 , , PUNCT cana-2813 53 5 particle particle NOUN cana-2813 53 6 swarm swarm NOUN cana-2813 53 7 optimization optimization NOUN cana-2813 53 8 ( ( PUNCT cana-2813 53 9 pso pso NOUN cana-2813 53 10 ) ) PUNCT cana-2813 54 1 [ [ X cana-2813 54 2 19 19 NUM cana-2813 54 3 ] ] PUNCT cana-2813 54 4 , , PUNCT cana-2813 54 5 and and CCONJ cana-2813 54 6 ant ant ADJ cana-2813 54 7 colony colony NOUN cana-2813 54 8 optimization optimization NOUN cana-2813 54 9 ( ( PUNCT cana-2813 54 10 aco aco PROPN cana-2813 54 11 ) ) PUNCT cana-2813 55 1 [ [ X cana-2813 55 2 20 20 NUM cana-2813 55 3 ] ] PUNCT cana-2813 55 4 have have AUX cana-2813 55 5 been be AUX cana-2813 55 6 employed employ VERB cana-2813 55 7 in in ADP cana-2813 55 8 feature feature NOUN cana-2813 55 9 selection selection NOUN cana-2813 55 10 and and CCONJ cana-2813 55 11 hyperparameter hyperparameter NOUN cana-2813 55 12 tuning tuning NOUN cana-2813 55 13 . . PUNCT cana-2813 56 1 while while SCONJ cana-2813 56 2 these these DET cana-2813 56 3 methods method NOUN cana-2813 56 4 have have AUX cana-2813 56 5 shown show VERB cana-2813 56 6 potential potential NOUN cana-2813 56 7 , , PUNCT cana-2813 56 8 they they PRON cana-2813 56 9 often often ADV cana-2813 56 10 face face VERB cana-2813 56 11 challenges challenge NOUN cana-2813 56 12 related relate VERB cana-2813 56 13 to to ADP cana-2813 56 14 convergence convergence NOUN cana-2813 56 15 speed speed NOUN cana-2813 56 16 and and CCONJ cana-2813 56 17 the the DET cana-2813 56 18 tendency tendency NOUN cana-2813 56 19 to to PART cana-2813 56 20 get get AUX cana-2813 56 21 trapped trap VERB cana-2813 56 22 in in ADP cana-2813 56 23 local local ADJ cana-2813 56 24 optima optima NOUN cana-2813 56 25 . . PUNCT cana-2813 57 1 the the DET cana-2813 57 2 mayfly mayfly NOUN cana-2813 57 3 optimization optimization NOUN cana-2813 57 4 algorithm algorithm NOUN cana-2813 57 5 offers offer VERB cana-2813 57 6 a a DET cana-2813 57 7 distinct distinct ADJ cana-2813 57 8 approach approach NOUN cana-2813 57 9 , , PUNCT cana-2813 57 10 with with ADP cana-2813 57 11 its its PRON cana-2813 57 12 ability ability NOUN cana-2813 57 13 to to PART cana-2813 57 14 proficiently proficiently ADV cana-2813 57 15 explore explore VERB cana-2813 57 16 the the DET cana-2813 57 17 search search NOUN cana-2813 57 18 space space NOUN cana-2813 57 19 and and CCONJ cana-2813 57 20 identify identify VERB cana-2813 57 21 promising promise VERB cana-2813 57 22 solutions solution NOUN cana-2813 57 23 [ [ X cana-2813 57 24 21 21 NUM cana-2813 57 25 ] ] PUNCT cana-2813 57 26 . . PUNCT cana-2813 58 1 despite despite SCONJ cana-2813 58 2 the the DET cana-2813 58 3 progress progress NOUN cana-2813 58 4 in in ADP cana-2813 58 5 ml ml PROPN cana-2813 58 6 , , PUNCT cana-2813 58 7 dl dl NOUN cana-2813 58 8 , , PUNCT cana-2813 58 9 and and CCONJ cana-2813 58 10 optimization optimization NOUN cana-2813 58 11 techniques technique NOUN cana-2813 58 12 , , PUNCT cana-2813 58 13 significant significant ADJ cana-2813 58 14 gaps gap NOUN cana-2813 58 15 remain remain VERB cana-2813 58 16 in in ADP cana-2813 58 17 their their PRON cana-2813 58 18 application application NOUN cana-2813 58 19 to to PART cana-2813 58 20 microarray microarray VERB cana-2813 58 21 gene gene NOUN cana-2813 58 22 expression expression NOUN cana-2813 58 23 data datum NOUN cana-2813 58 24 classification classification NOUN cana-2813 58 25 . . PUNCT cana-2813 59 1 while while SCONJ cana-2813 59 2 dnabert dnabert PROPN cana-2813 59 3 offers offer VERB cana-2813 59 4 powerful powerful ADJ cana-2813 59 5 capabilities capability NOUN cana-2813 59 6 for for ADP cana-2813 59 7 genomic genomic ADJ cana-2813 59 8 data datum NOUN cana-2813 59 9 analysis analysis NOUN cana-2813 59 10 , , PUNCT cana-2813 59 11 optimizing optimize VERB cana-2813 59 12 its its PRON cana-2813 59 13 performance performance NOUN cana-2813 59 14 through through ADP cana-2813 59 15 effective effective ADJ cana-2813 59 16 feature feature NOUN cana-2813 59 17 selection selection NOUN cana-2813 59 18 and and CCONJ cana-2813 59 19 hyperparameter hyperparameter NOUN cana-2813 59 20 tuning tuning NOUN cana-2813 59 21 remains remain VERB cana-2813 59 22 a a DET cana-2813 59 23 challenge challenge NOUN cana-2813 59 24 . . PUNCT cana-2813 60 1 this this DET cana-2813 60 2 research research NOUN cana-2813 60 3 aims aim VERB cana-2813 60 4 to to PART cana-2813 60 5 address address VERB cana-2813 60 6 these these DET cana-2813 60 7 gaps gap NOUN cana-2813 60 8 by by ADP cana-2813 60 9 integrating integrate VERB cana-2813 60 10 mfo mfo PROPN cana-2813 60 11 with with ADP cana-2813 60 12 dnabert dnabert NOUN cana-2813 60 13 , , PUNCT cana-2813 60 14 creating create VERB cana-2813 60 15 a a DET cana-2813 60 16 novel novel ADJ cana-2813 60 17 framework framework NOUN cana-2813 60 18 for for ADP cana-2813 60 19 microarray microarray NOUN cana-2813 60 20 gene gene NOUN cana-2813 60 21 expression expression NOUN cana-2813 60 22 data datum NOUN cana-2813 60 23 classification classification NOUN cana-2813 60 24 . . PUNCT cana-2813 61 1 the the DET cana-2813 61 2 aims aim NOUN cana-2813 61 3 of of ADP cana-2813 61 4 this this DET cana-2813 61 5 research research NOUN cana-2813 61 6 are be AUX cana-2813 61 7 to to PART cana-2813 61 8 develop develop VERB cana-2813 61 9 an an DET cana-2813 61 10 automated automate VERB cana-2813 61 11 classification classification NOUN cana-2813 61 12 approach approach NOUN cana-2813 61 13 using use VERB cana-2813 61 14 deep deep ADJ cana-2813 61 15 learning learning NOUN cana-2813 61 16 and and CCONJ cana-2813 61 17 mfo mfo PROPN cana-2813 61 18 , , PUNCT cana-2813 61 19 and and CCONJ cana-2813 61 20 to to PART cana-2813 61 21 demonstrate demonstrate VERB cana-2813 61 22 its its PRON cana-2813 61 23 effectiveness effectiveness NOUN cana-2813 61 24 on on ADP cana-2813 61 25 various various ADJ cana-2813 61 26 datasets dataset NOUN cana-2813 61 27 , , PUNCT cana-2813 61 28 including include VERB cana-2813 61 29 those those PRON cana-2813 61 30 from from ADP cana-2813 61 31 acute acute ADJ cana-2813 61 32 myeloid myeloid NOUN cana-2813 61 33 leukemia leukemia NOUN cana-2813 61 34 ( ( PUNCT cana-2813 61 35 aml aml PROPN cana-2813 61 36 ) ) PUNCT cana-2813 61 37 and and CCONJ cana-2813 61 38 acute acute ADJ cana-2813 61 39 lymphoblastic lymphoblastic ADJ cana-2813 61 40 leukemia leukemia NOUN cana-2813 61 41 ( ( PUNCT cana-2813 61 42 all all DET cana-2813 61 43 ) ) PUNCT cana-2813 61 44 data datum NOUN cana-2813 61 45 . . PUNCT cana-2813 62 1 by by ADP cana-2813 62 2 combining combine VERB cana-2813 62 3 mfo mfo PROPN cana-2813 62 4 with with ADP cana-2813 62 5 dnabert dnabert NOUN cana-2813 62 6 , , PUNCT cana-2813 62 7 this this DET cana-2813 62 8 research research NOUN cana-2813 62 9 seeks seek VERB cana-2813 62 10 to to PART cana-2813 62 11 advance advance VERB cana-2813 62 12 the the DET cana-2813 62 13 state state NOUN cana-2813 62 14 of of ADP cana-2813 62 15 the the DET cana-2813 62 16 art art NOUN cana-2813 62 17 in in ADP cana-2813 62 18 microarray microarray NOUN cana-2813 62 19 gene gene NOUN cana-2813 62 20 expression expression NOUN cana-2813 62 21 data datum NOUN cana-2813 62 22 classification classification NOUN cana-2813 62 23 , , PUNCT cana-2813 62 24 offering offer VERB cana-2813 62 25 a a DET cana-2813 62 26 robust robust ADJ cana-2813 62 27 tool tool NOUN cana-2813 62 28 for for ADP cana-2813 62 29 both both CCONJ cana-2813 62 30 research research NOUN cana-2813 62 31 and and CCONJ cana-2813 62 32 clinical clinical ADJ cana-2813 62 33 applications application NOUN cana-2813 62 34 . . PUNCT cana-2813 63 1 this this DET cana-2813 63 2 integration integration NOUN cana-2813 63 3 leverages leverage VERB cana-2813 63 4 the the DET cana-2813 63 5 strengths strength NOUN cana-2813 63 6 of of ADP cana-2813 63 7 both both DET cana-2813 63 8 optimization optimization NOUN cana-2813 63 9 algorithms algorithm NOUN cana-2813 63 10 and and CCONJ cana-2813 63 11 deep deep ADJ cana-2813 63 12 learning learning NOUN cana-2813 63 13 models model NOUN cana-2813 63 14 to to PART cana-2813 63 15 create create VERB cana-2813 63 16 a a DET cana-2813 63 17 unified unified ADJ cana-2813 63 18 framework framework NOUN cana-2813 63 19 that that PRON cana-2813 63 20 enhances enhance VERB cana-2813 63 21 classification classification NOUN cana-2813 63 22 accuracy accuracy NOUN cana-2813 63 23 and and CCONJ cana-2813 63 24 robustness robustness NOUN cana-2813 63 25 . . PUNCT cana-2813 64 1 2 2 X cana-2813 64 2 . . X cana-2813 64 3 methodology methodology NOUN cana-2813 64 4 the the DET cana-2813 64 5 methodology methodology NOUN cana-2813 64 6 of of ADP cana-2813 64 7 this this DET cana-2813 64 8 research research NOUN cana-2813 64 9 focuses focus VERB cana-2813 64 10 on on ADP cana-2813 64 11 developing develop VERB cana-2813 64 12 an an DET cana-2813 64 13 automated automate VERB cana-2813 64 14 classification classification NOUN cana-2813 64 15 approach approach NOUN cana-2813 64 16 that that PRON cana-2813 64 17 integrates integrate VERB cana-2813 64 18 deep deep ADJ cana-2813 64 19 learning learning NOUN cana-2813 64 20 with with ADP cana-2813 64 21 the the DET cana-2813 64 22 mayfly mayfly NOUN cana-2813 64 23 optimization optimization NOUN cana-2813 64 24 algorithm algorithm NOUN cana-2813 64 25 ( ( PUNCT cana-2813 64 26 mfo mfo NOUN cana-2813 64 27 ) ) PUNCT cana-2813 64 28 to to PART cana-2813 64 29 improve improve VERB cana-2813 64 30 the the DET cana-2813 64 31 accuracy accuracy NOUN cana-2813 64 32 and and CCONJ cana-2813 64 33 robustness robustness NOUN cana-2813 64 34 of of ADP cana-2813 64 35 microarray microarray ADJ cana-2813 64 36 gene gene NOUN cana-2813 64 37 expression expression NOUN cana-2813 64 38 data datum NOUN cana-2813 64 39 classification classification NOUN cana-2813 64 40 . . PUNCT cana-2813 65 1 the the DET cana-2813 65 2 dataset dataset NOUN cana-2813 65 3 used use VERB cana-2813 65 4 in in ADP cana-2813 65 5 this this DET cana-2813 65 6 study study NOUN cana-2813 65 7 , , PUNCT cana-2813 65 8 which which PRON cana-2813 65 9 includes include VERB cana-2813 65 10 five five NUM cana-2813 65 11 types type NOUN cana-2813 65 12 of of ADP cana-2813 65 13 cancer cancer NOUN cana-2813 65 14 , , PUNCT cana-2813 65 15 was be AUX cana-2813 65 16 collected collect VERB cana-2813 65 17 from from ADP cana-2813 65 18 the the DET cana-2813 65 19 work work NOUN cana-2813 65 20 titled title VERB cana-2813 65 21 " " PUNCT cana-2813 65 22 markov markov NOUN cana-2813 65 23 blanket blanket NOUN cana-2813 65 24 - - PUNCT cana-2813 65 25 embedded embed VERB cana-2813 65 26 genetic genetic ADJ cana-2813 65 27 algorithm algorithm NOUN cana-2813 65 28 for for ADP cana-2813 65 29 gene gene NOUN cana-2813 65 30 selection selection NOUN cana-2813 65 31 " " PUNCT cana-2813 65 32 [ [ X cana-2813 65 33 22 22 NUM cana-2813 65 34 ] ] PUNCT cana-2813 65 35 . . PUNCT cana-2813 66 1 by by ADP cana-2813 66 2 combining combine VERB cana-2813 66 3 mfo mfo PROPN cana-2813 66 4 with with ADP cana-2813 66 5 dnabert dnabert NOUN cana-2813 66 6 , , PUNCT cana-2813 66 7 the the DET cana-2813 66 8 research research NOUN cana-2813 66 9 aims aim VERB cana-2813 66 10 to to PART cana-2813 66 11 advance advance VERB cana-2813 66 12 the the DET cana-2813 66 13 current current ADJ cana-2813 66 14 state state NOUN cana-2813 66 15 of of ADP cana-2813 66 16 the the DET cana-2813 66 17 art art NOUN cana-2813 66 18 in in ADP cana-2813 66 19 gene gene NOUN cana-2813 66 20 expression expression NOUN cana-2813 66 21 data datum NOUN cana-2813 66 22 classification classification NOUN cana-2813 66 23 . . PUNCT cana-2813 67 1 this this DET cana-2813 67 2 unified unify VERB cana-2813 67 3 framework framework NOUN cana-2813 67 4 leverages leverage VERB cana-2813 67 5 the the DET cana-2813 67 6 strengths strength NOUN cana-2813 67 7 of of ADP cana-2813 67 8 both both DET cana-2813 67 9 optimization optimization NOUN cana-2813 67 10 algorithms algorithm NOUN cana-2813 67 11 and and CCONJ cana-2813 67 12 deep deep ADJ cana-2813 67 13 learning learning NOUN cana-2813 67 14 models model NOUN cana-2813 67 15 , , PUNCT cana-2813 67 16 offering offer VERB cana-2813 67 17 a a DET cana-2813 67 18 robust robust ADJ cana-2813 67 19 tool tool NOUN cana-2813 67 20 for for ADP cana-2813 67 21 research research NOUN cana-2813 67 22 and and CCONJ cana-2813 67 23 clinical clinical ADJ cana-2813 67 24 applications application NOUN cana-2813 67 25 , , PUNCT cana-2813 67 26 particularly particularly ADV cana-2813 67 27 in in ADP cana-2813 67 28 the the DET cana-2813 67 29 classification classification NOUN cana-2813 67 30 of of ADP cana-2813 67 31 various various ADJ cana-2813 67 32 cancer cancer NOUN cana-2813 67 33 types type NOUN cana-2813 67 34 . . PUNCT cana-2813 68 1 2.1 2.1 NUM cana-2813 68 2 . . PUNCT cana-2813 68 3 model model NOUN cana-2813 68 4 implementation implementation NOUN cana-2813 68 5 transfer transfer NOUN cana-2813 68 6 learning learn VERB cana-2813 68 7 dna dna PROPN cana-2813 68 8 bidirectional bidirectional ADJ cana-2813 68 9 encoder encoder NOUN cana-2813 68 10 representations representation VERB cana-2813 68 11 transformers transformer NOUN cana-2813 68 12 ( ( PUNCT cana-2813 68 13 bert bert PROPN cana-2813 68 14 ) ) PUNCT cana-2813 68 15 model model NOUN cana-2813 68 16 , , PUNCT cana-2813 68 17 mayfly mayfly NOUN cana-2813 68 18 optimization optimization NOUN cana-2813 68 19 algorithm algorithm NOUN cana-2813 68 20 ( ( PUNCT cana-2813 68 21 mfo mfo NOUN cana-2813 68 22 ) ) PUNCT cana-2813 68 23 model model NOUN cana-2813 68 24 , , PUNCT cana-2813 68 25 and and CCONJ cana-2813 68 26 the the DET cana-2813 68 27 fusion fusion NOUN cana-2813 68 28 of of ADP cana-2813 68 29 them they PRON cana-2813 68 30 are be AUX cana-2813 68 31 used use VERB cana-2813 68 32 for for ADP cana-2813 68 33 this this DET cana-2813 68 34 application application NOUN cana-2813 68 35 . . PUNCT cana-2813 69 1 the the DET cana-2813 69 2 overview overview NOUN cana-2813 69 3 of of ADP cana-2813 69 4 these these DET cana-2813 69 5 models model NOUN cana-2813 69 6 are be AUX cana-2813 69 7 explained explain VERB cana-2813 69 8 in in ADP cana-2813 69 9 this this DET cana-2813 69 10 section section NOUN cana-2813 69 11 . . PUNCT cana-2813 70 1 communications communication NOUN cana-2813 70 2 on on ADP cana-2813 70 3 applied apply VERB cana-2813 70 4 nonlinear nonlinear ADJ cana-2813 70 5 analysis analysis NOUN cana-2813 70 6 issn issn NOUN cana-2813 70 7 : : PUNCT cana-2813 70 8 1074 1074 NUM cana-2813 70 9 - - PUNCT cana-2813 70 10 133x 133x NUM cana-2813 70 11 vol vol NOUN cana-2813 70 12 32 32 NUM cana-2813 70 13 no no NOUN cana-2813 70 14 . . PUNCT cana-2813 71 1 4s 4s NUM cana-2813 71 2 ( ( PUNCT cana-2813 71 3 2025 2025 NUM cana-2813 71 4 ) ) PUNCT cana-2813 71 5 273 273 NUM cana-2813 71 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 71 7 2.1.1 2.1.1 NUM cana-2813 71 8 . . PUNCT cana-2813 71 9 dnabert dnabert PROPN cana-2813 71 10 dnabert dnabert PROPN cana-2813 71 11 represents represent VERB cana-2813 71 12 a a DET cana-2813 71 13 significant significant ADJ cana-2813 71 14 advancement advancement NOUN cana-2813 71 15 in in ADP cana-2813 71 16 the the DET cana-2813 71 17 deep deep ADJ cana-2813 71 18 learning learning NOUN cana-2813 71 19 application application NOUN cana-2813 71 20 to to ADP cana-2813 71 21 genomic genomic ADJ cana-2813 71 22 data datum NOUN cana-2813 71 23 , , PUNCT cana-2813 71 24 extending extend VERB cana-2813 71 25 the the DET cana-2813 71 26 success success NOUN cana-2813 71 27 of of ADP cana-2813 71 28 bert bert PROPN cana-2813 71 29 ( ( PUNCT cana-2813 71 30 bidirectional bidirectional ADJ cana-2813 71 31 encoder encoder NOUN cana-2813 71 32 representations representation VERB cana-2813 71 33 from from ADP cana-2813 71 34 transformers transformer NOUN cana-2813 71 35 ) ) PUNCT cana-2813 71 36 to to ADP cana-2813 71 37 bioinformatics bioinformatics NOUN cana-2813 71 38 [ [ X cana-2813 71 39 23 23 NUM cana-2813 71 40 ] ] PUNCT cana-2813 71 41 . . PUNCT cana-2813 72 1 dnabert dnabert ADJ cana-2813 72 2 leverages leverage VERB cana-2813 72 3 a a DET cana-2813 72 4 transformer transformer NOUN cana-2813 72 5 - - PUNCT cana-2813 72 6 based base VERB cana-2813 72 7 architecture architecture NOUN cana-2813 72 8 renowned renowne VERB cana-2813 72 9 for for ADP cana-2813 72 10 its its PRON cana-2813 72 11 capability capability NOUN cana-2813 72 12 to to PART cana-2813 72 13 capture capture VERB cana-2813 72 14 complex complex ADJ cana-2813 72 15 relationships relationship NOUN cana-2813 72 16 within within ADP cana-2813 72 17 data datum NOUN cana-2813 72 18 . . PUNCT cana-2813 73 1 it it PRON cana-2813 73 2 is be AUX cana-2813 73 3 pretrained pretraine VERB cana-2813 73 4 on on ADP cana-2813 73 5 large large ADJ cana-2813 73 6 - - PUNCT cana-2813 73 7 scale scale NOUN cana-2813 73 8 genomic genomic NOUN cana-2813 73 9 sequences sequence NOUN cana-2813 73 10 , , PUNCT cana-2813 73 11 enabling enable VERB cana-2813 73 12 the the DET cana-2813 73 13 model model NOUN cana-2813 73 14 to to PART cana-2813 73 15 learn learn VERB cana-2813 73 16 contextual contextual ADJ cana-2813 73 17 embeddings embedding NOUN cana-2813 73 18 for for ADP cana-2813 73 19 dna dna PROPN cana-2813 73 20 sequences sequence NOUN cana-2813 73 21 . . PUNCT cana-2813 74 1 this this DET cana-2813 74 2 bidirectional bidirectional ADJ cana-2813 74 3 approach approach NOUN cana-2813 74 4 allows allow VERB cana-2813 74 5 dnabert dnabert PROPN cana-2813 74 6 to to PART cana-2813 74 7 understand understand VERB cana-2813 74 8 interactions interaction NOUN cana-2813 74 9 between between ADP cana-2813 74 10 different different ADJ cana-2813 74 11 genes gene NOUN cana-2813 74 12 more more ADV cana-2813 74 13 comprehensively comprehensively ADV cana-2813 74 14 by by ADP cana-2813 74 15 processing process VERB cana-2813 74 16 their their PRON cana-2813 74 17 sequences sequence NOUN cana-2813 74 18 in in ADP cana-2813 74 19 both both DET cana-2813 74 20 directions direction NOUN cana-2813 74 21 . . PUNCT cana-2813 75 1 the the DET cana-2813 75 2 self self NOUN cana-2813 75 3 - - PUNCT cana-2813 75 4 attention attention NOUN cana-2813 75 5 mechanism mechanism NOUN cana-2813 75 6 at at ADP cana-2813 75 7 the the DET cana-2813 75 8 core core NOUN cana-2813 75 9 of of ADP cana-2813 75 10 dnabert dnabert NOUN cana-2813 75 11 is be AUX cana-2813 75 12 mathematically mathematically ADV cana-2813 75 13 described describe VERB cana-2813 75 14 by by ADP cana-2813 75 15 the the DET cana-2813 75 16 following follow VERB cana-2813 75 17 equation equation NOUN cana-2813 75 18 : : PUNCT cana-2813 75 19 π΄π‘‘π‘‘π‘’π‘›π‘‘π‘–π‘œπ‘›(𝑄 π΄π‘‘π‘‘π‘’π‘›π‘‘π‘–π‘œπ‘›(𝑄 PROPN cana-2813 75 20 , , PUNCT cana-2813 75 21 𝐾 𝐾 PROPN cana-2813 75 22 , , PUNCT cana-2813 75 23 𝑉 𝑉 PROPN cana-2813 75 24 ) ) PUNCT cana-2813 75 25 = = VERB cana-2813 75 26 π‘ π‘œπ‘“π‘‘π‘šπ‘Žπ‘₯ π‘ π‘œπ‘“π‘‘π‘šπ‘Žπ‘₯ NOUN cana-2813 75 27 ( ( PUNCT cana-2813 75 28 𝑄𝐾𝑇 𝑄𝐾𝑇 NOUN cana-2813 75 29 βˆšπ‘‘π‘˜ βˆšπ‘‘π‘˜ PROPN cana-2813 75 30 ) ) PUNCT cana-2813 76 1 𝑉 𝑉 PROPN cana-2813 76 2 equation equation NOUN cana-2813 76 3 1 1 NUM cana-2813 76 4 where where SCONJ cana-2813 76 5 q q X cana-2813 76 6 , , PUNCT cana-2813 76 7 k k NOUN cana-2813 76 8 , , PUNCT cana-2813 76 9 and and CCONJ cana-2813 76 10 v v X cana-2813 76 11 represent represent VERB cana-2813 76 12 the the DET cana-2813 76 13 query query NOUN cana-2813 76 14 , , PUNCT cana-2813 76 15 key key ADJ cana-2813 76 16 , , PUNCT cana-2813 76 17 and and CCONJ cana-2813 76 18 value value NOUN cana-2813 76 19 matrices matrix NOUN cana-2813 76 20 , , PUNCT cana-2813 76 21 respectively respectively ADV cana-2813 76 22 , , PUNCT cana-2813 76 23 and and CCONJ cana-2813 76 24 dk dk PROPN cana-2813 76 25 is be AUX cana-2813 76 26 the the DET cana-2813 76 27 key key ADJ cana-2813 76 28 vectors vector NOUN cana-2813 76 29 dimensionality dimensionality NOUN cana-2813 76 30 [ [ X cana-2813 76 31 24 24 NUM cana-2813 76 32 ] ] PUNCT cana-2813 76 33 . . PUNCT cana-2813 77 1 this this DET cana-2813 77 2 mechanism mechanism NOUN cana-2813 77 3 enables enable VERB cana-2813 77 4 dnabert dnabert ADJ cana-2813 77 5 to to PART cana-2813 77 6 focus focus VERB cana-2813 77 7 on on ADP cana-2813 77 8 the the DET cana-2813 77 9 most most ADV cana-2813 77 10 relevant relevant ADJ cana-2813 77 11 gene gene NOUN cana-2813 77 12 interactions interaction NOUN cana-2813 77 13 , , PUNCT cana-2813 77 14 which which PRON cana-2813 77 15 is be AUX cana-2813 77 16 crucial crucial ADJ cana-2813 77 17 for for ADP cana-2813 77 18 accurate accurate ADJ cana-2813 77 19 classification classification NOUN cana-2813 77 20 tasks task NOUN cana-2813 77 21 in in ADP cana-2813 77 22 genomics genomics NOUN cana-2813 77 23 . . PUNCT cana-2813 78 1 fig fig NOUN cana-2813 78 2 . . PUNCT cana-2813 79 1 1 1 NUM cana-2813 79 2 : : PUNCT cana-2813 79 3 dnabert dnabert PROPN cana-2813 79 4 uses use VERB cana-2813 79 5 tokenized tokenized ADJ cana-2813 79 6 input input NOUN cana-2813 79 7 that that PRON cana-2813 79 8 passes pass VERB cana-2813 79 9 the the DET cana-2813 79 10 embedding embed VERB cana-2813 79 11 layer layer NOUN cana-2813 79 12 and and CCONJ cana-2813 79 13 is be AUX cana-2813 79 14 fed feed VERB cana-2813 79 15 to to PART cana-2813 79 16 transformer transformer VERB cana-2813 79 17 blocks block NOUN cana-2813 79 18 . . PUNCT cana-2813 80 1 the the DET cana-2813 80 2 first first ADJ cana-2813 80 3 output output NOUN cana-2813 80 4 among among ADP cana-2813 80 5 last last ADJ cana-2813 80 6 hidden hide VERB cana-2813 80 7 states state NOUN cana-2813 80 8 are be AUX cana-2813 80 9 used use VERB cana-2813 80 10 for for ADP cana-2813 80 11 sentence sentence NOUN cana-2813 80 12 - - PUNCT cana-2813 80 13 level level NOUN cana-2813 80 14 classification classification NOUN cana-2813 80 15 while while SCONJ cana-2813 80 16 outputs output NOUN cana-2813 80 17 for for ADP cana-2813 80 18 individual individual ADJ cana-2813 80 19 masked mask VERB cana-2813 80 20 tokens token NOUN cana-2813 80 21 are be AUX cana-2813 80 22 used use VERB cana-2813 80 23 for for ADP cana-2813 80 24 token token VERB cana-2813 80 25 - - PUNCT cana-2813 80 26 level level NOUN cana-2813 80 27 classification classification NOUN cana-2813 81 1 [ [ X cana-2813 81 2 33 33 NUM cana-2813 81 3 ] ] PUNCT cana-2813 81 4 . . PUNCT cana-2813 82 1 communications communication NOUN cana-2813 82 2 on on ADP cana-2813 82 3 applied apply VERB cana-2813 82 4 nonlinear nonlinear ADJ cana-2813 82 5 analysis analysis NOUN cana-2813 82 6 issn issn NOUN cana-2813 82 7 : : PUNCT cana-2813 82 8 1074 1074 NUM cana-2813 82 9 - - PUNCT cana-2813 82 10 133x 133x NUM cana-2813 82 11 vol vol NOUN cana-2813 82 12 32 32 NUM cana-2813 82 13 no no NOUN cana-2813 82 14 . . PUNCT cana-2813 83 1 4s 4s NUM cana-2813 83 2 ( ( PUNCT cana-2813 83 3 2025 2025 NUM cana-2813 83 4 ) ) PUNCT cana-2813 83 5 274 274 NUM cana-2813 83 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 83 7 2.1.2 2.1.2 NUM cana-2813 83 8 . . PUNCT cana-2813 83 9 mayfly mayfly NOUN cana-2813 83 10 optimization optimization NOUN cana-2813 83 11 algorithm algorithm NOUN cana-2813 83 12 ( ( PUNCT cana-2813 83 13 mfo mfo PROPN cana-2813 83 14 ) ) PUNCT cana-2813 83 15 the the DET cana-2813 83 16 mayfly mayfly NOUN cana-2813 83 17 optimization optimization NOUN cana-2813 83 18 algorithm algorithm NOUN cana-2813 83 19 ( ( PUNCT cana-2813 83 20 mfo mfo NOUN cana-2813 83 21 ) ) PUNCT cana-2813 83 22 is be AUX cana-2813 83 23 a a DET cana-2813 83 24 bio bio ADJ cana-2813 83 25 - - PUNCT cana-2813 83 26 inspired inspire VERB cana-2813 83 27 optimization optimization NOUN cana-2813 83 28 technique technique NOUN cana-2813 83 29 that that PRON cana-2813 83 30 mimics mimic VERB cana-2813 83 31 the the DET cana-2813 83 32 swarming swarm VERB cana-2813 83 33 and and CCONJ cana-2813 83 34 mating mating NOUN cana-2813 83 35 behavior behavior NOUN cana-2813 83 36 of of ADP cana-2813 83 37 mayflies mayfly NOUN cana-2813 83 38 to to PART cana-2813 83 39 tackle tackle VERB cana-2813 83 40 complex complex ADJ cana-2813 83 41 optimization optimization NOUN cana-2813 83 42 problems problem NOUN cana-2813 83 43 [ [ X cana-2813 83 44 25 25 NUM cana-2813 83 45 ] ] PUNCT cana-2813 83 46 . . PUNCT cana-2813 84 1 mfo mfo PROPN cana-2813 84 2 efficiently efficiently ADV cana-2813 84 3 explores explore VERB cana-2813 84 4 high high ADJ cana-2813 84 5 - - PUNCT cana-2813 84 6 dimensional dimensional ADJ cana-2813 84 7 search search NOUN cana-2813 84 8 spaces space NOUN cana-2813 84 9 by by ADP cana-2813 84 10 balancing balance VERB cana-2813 84 11 exploration exploration NOUN cana-2813 84 12 ( ( PUNCT cana-2813 84 13 probing probe VERB cana-2813 84 14 new new ADJ cana-2813 84 15 areas area NOUN cana-2813 84 16 ) ) PUNCT cana-2813 84 17 and and CCONJ cana-2813 84 18 exploitation exploitation NOUN cana-2813 84 19 ( ( PUNCT cana-2813 84 20 refining refining NOUN cana-2813 84 21 recognized recognize VERB cana-2813 84 22 good good ADJ cana-2813 84 23 solutions solution NOUN cana-2813 84 24 ) ) PUNCT cana-2813 84 25 . . PUNCT cana-2813 85 1 the the DET cana-2813 85 2 algorithm algorithm NOUN cana-2813 85 3 begins begin VERB cana-2813 85 4 with with ADP cana-2813 85 5 the the DET cana-2813 85 6 initialization initialization NOUN cana-2813 85 7 of of ADP cana-2813 85 8 a a DET cana-2813 85 9 population population NOUN cana-2813 85 10 of of ADP cana-2813 85 11 mayflies mayfly NOUN cana-2813 85 12 in in ADP cana-2813 85 13 the the DET cana-2813 85 14 search search NOUN cana-2813 85 15 space space NOUN cana-2813 85 16 . . PUNCT cana-2813 86 1 as as SCONJ cana-2813 86 2 the the DET cana-2813 86 3 algorithm algorithm NOUN cana-2813 86 4 progresses progress VERB cana-2813 86 5 , , PUNCT cana-2813 86 6 mayflies mayfly NOUN cana-2813 86 7 move move VERB cana-2813 86 8 based base VERB cana-2813 86 9 on on ADP cana-2813 86 10 their their PRON cana-2813 86 11 fitness fitness NOUN cana-2813 86 12 and and CCONJ cana-2813 86 13 the the DET cana-2813 86 14 positions position NOUN cana-2813 86 15 of of ADP cana-2813 86 16 others other NOUN cana-2813 86 17 . . PUNCT cana-2813 87 1 the the DET cana-2813 87 2 mating mating NOUN cana-2813 87 3 process process NOUN cana-2813 87 4 further far ADV cana-2813 87 5 refines refine VERB cana-2813 87 6 their their PRON cana-2813 87 7 positions position NOUN cana-2813 87 8 , , PUNCT cana-2813 87 9 simulating simulate VERB cana-2813 87 10 natural natural ADJ cana-2813 87 11 selection selection NOUN cana-2813 87 12 . . PUNCT cana-2813 88 1 the the DET cana-2813 88 2 position position NOUN cana-2813 88 3 update update NOUN cana-2813 88 4 of of ADP cana-2813 88 5 a a DET cana-2813 88 6 mayfly mayfly NOUN cana-2813 88 7 i i PRON cana-2813 88 8 is be AUX cana-2813 88 9 governed govern VERB cana-2813 88 10 by by ADP cana-2813 88 11 the the DET cana-2813 88 12 equation equation NOUN cana-2813 88 13 : : PUNCT cana-2813 89 1 π‘π‘’π‘€π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘›π‘– π‘π‘’π‘€π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘›π‘– PROPN cana-2813 89 2 = = SYM cana-2813 90 1 π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘›π‘– π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘›π‘– PROPN cana-2813 90 2 + + NUM cana-2813 90 3 𝛼. 𝛼. NOUN cana-2813 90 4 ( ( PUNCT cana-2813 90 5 π΅π‘’π‘ π‘‘π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘› π΅π‘’π‘ π‘‘π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘› PROPN cana-2813 90 6 βˆ’ βˆ’ PROPN cana-2813 90 7 π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘›π‘– π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘œπ‘›π‘– PROPN cana-2813 90 8 ) ) PUNCT cana-2813 90 9 equation equation NOUN cana-2813 90 10 2 2 NUM cana-2813 90 11 where where SCONJ cana-2813 90 12 Ξ± Ξ± NOUN cana-2813 90 13 is be AUX cana-2813 90 14 a a DET cana-2813 90 15 step step NOUN cana-2813 90 16 size size NOUN cana-2813 90 17 parameter parameter NOUN cana-2813 90 18 , , PUNCT cana-2813 90 19 and and CCONJ cana-2813 90 20 bestposition bestposition NOUN cana-2813 90 21 denotes denote VERB cana-2813 90 22 the the DET cana-2813 90 23 optimal optimal ADJ cana-2813 90 24 position position NOUN cana-2813 90 25 discovered discover VERB cana-2813 90 26 by by ADP cana-2813 90 27 the the DET cana-2813 90 28 mayflies mayfly NOUN cana-2813 90 29 [ [ X cana-2813 90 30 26 26 NUM cana-2813 90 31 ] ] PUNCT cana-2813 90 32 . . PUNCT cana-2813 91 1 this this DET cana-2813 91 2 formulation formulation NOUN cana-2813 91 3 directs direct VERB cana-2813 91 4 the the DET cana-2813 91 5 pursuit pursuit NOUN cana-2813 91 6 towards towards ADP cana-2813 91 7 promising promising ADJ cana-2813 91 8 regions region NOUN cana-2813 91 9 of of ADP cana-2813 91 10 the the DET cana-2813 91 11 space space NOUN cana-2813 91 12 , , PUNCT cana-2813 91 13 enhancing enhance VERB cana-2813 91 14 the the DET cana-2813 91 15 likelihood likelihood NOUN cana-2813 91 16 of of ADP cana-2813 91 17 finding find VERB cana-2813 91 18 optimal optimal ADJ cana-2813 91 19 solutions solution NOUN cana-2813 91 20 . . PUNCT cana-2813 92 1 2.1.3 2.1.3 X cana-2813 92 2 . . PUNCT cana-2813 92 3 integration integration NOUN cana-2813 92 4 of of ADP cana-2813 92 5 mfo mfo PROPN cana-2813 92 6 with with ADP cana-2813 92 7 dnabert dnabert PROPN cana-2813 92 8 the the DET cana-2813 92 9 proposed propose VERB cana-2813 92 10 method method NOUN cana-2813 92 11 integrates integrate VERB cana-2813 92 12 mfo mfo PROPN cana-2813 92 13 with with ADP cana-2813 92 14 dnabert dnabert NOUN cana-2813 92 15 to to PART cana-2813 92 16 enhance enhance VERB cana-2813 92 17 the the DET cana-2813 92 18 classification classification NOUN cana-2813 92 19 performance performance NOUN cana-2813 92 20 of of ADP cana-2813 92 21 deep deep ADJ cana-2813 92 22 learning learning NOUN cana-2813 92 23 models model NOUN cana-2813 92 24 applied apply VERB cana-2813 92 25 to to ADP cana-2813 92 26 microarray microarray NOUN cana-2813 92 27 gene gene NOUN cana-2813 92 28 expression expression NOUN cana-2813 92 29 data datum NOUN cana-2813 92 30 . . PUNCT cana-2813 93 1 this this DET cana-2813 93 2 integration integration NOUN cana-2813 93 3 addresses address VERB cana-2813 93 4 key key ADJ cana-2813 93 5 challenges challenge NOUN cana-2813 93 6 in in ADP cana-2813 93 7 gene gene NOUN cana-2813 93 8 expression expression NOUN cana-2813 93 9 data datum NOUN cana-2813 93 10 analysis analysis NOUN cana-2813 93 11 , , PUNCT cana-2813 93 12 including include VERB cana-2813 93 13 feature feature NOUN cana-2813 93 14 selection selection NOUN cana-2813 93 15 and and CCONJ cana-2813 93 16 hyperparameter hyperparameter NOUN cana-2813 93 17 tuning tuning NOUN cana-2813 93 18 . . PUNCT cana-2813 94 1 firstly firstly ADV cana-2813 94 2 , , PUNCT cana-2813 94 3 feature feature NOUN cana-2813 94 4 selection selection NOUN cana-2813 94 5 is be AUX cana-2813 94 6 crucial crucial ADJ cana-2813 94 7 due due ADP cana-2813 94 8 to to ADP cana-2813 94 9 the the DET cana-2813 94 10 high high ADJ cana-2813 94 11 dimensionality dimensionality NOUN cana-2813 94 12 of of ADP cana-2813 94 13 microarray microarray NOUN cana-2813 94 14 gene gene NOUN cana-2813 94 15 expression expression NOUN cana-2813 94 16 data datum NOUN cana-2813 94 17 , , PUNCT cana-2813 94 18 where where SCONJ cana-2813 94 19 the the DET cana-2813 94 20 number number NOUN cana-2813 94 21 of of ADP cana-2813 94 22 features feature NOUN cana-2813 94 23 ( ( PUNCT cana-2813 94 24 genes gene NOUN cana-2813 94 25 ) ) PUNCT cana-2813 94 26 greatly greatly ADV cana-2813 94 27 surpasses surpass VERB cana-2813 94 28 the the DET cana-2813 94 29 number number NOUN cana-2813 94 30 of of ADP cana-2813 94 31 samples sample NOUN cana-2813 94 32 . . PUNCT cana-2813 95 1 mfo mfo PROPN cana-2813 95 2 is be AUX cana-2813 95 3 employed employ VERB cana-2813 95 4 to to PART cana-2813 95 5 identify identify VERB cana-2813 95 6 the the DET cana-2813 95 7 most most ADV cana-2813 95 8 relevant relevant ADJ cana-2813 95 9 gene gene NOUN cana-2813 95 10 subsets subset NOUN cana-2813 95 11 for for ADP cana-2813 95 12 classification classification NOUN cana-2813 95 13 . . PUNCT cana-2813 96 1 the the DET cana-2813 96 2 feature feature NOUN cana-2813 96 3 selection selection NOUN cana-2813 96 4 process process NOUN cana-2813 96 5 is be AUX cana-2813 96 6 framed frame VERB cana-2813 96 7 as as ADP cana-2813 96 8 an an DET cana-2813 96 9 optimization optimization NOUN cana-2813 96 10 problem problem NOUN cana-2813 96 11 where where SCONJ cana-2813 96 12 the the DET cana-2813 96 13 objective objective ADJ cana-2813 96 14 function function NOUN cana-2813 96 15 f(s f( VERB cana-2813 96 16 ) ) PUNCT cana-2813 96 17 represents represent VERB cana-2813 96 18 the the DET cana-2813 96 19 classification classification NOUN cana-2813 96 20 performance performance NOUN cana-2813 96 21 based base VERB cana-2813 96 22 on on ADP cana-2813 96 23 a a DET cana-2813 96 24 gene gene NOUN cana-2813 96 25 subset subset NOUN cana-2813 96 26 sss sss PROPN cana-2813 96 27 . . PUNCT cana-2813 96 28 mfo mfo PROPN cana-2813 96 29 optimizes optimize VERB cana-2813 96 30 this this DET cana-2813 96 31 function function NOUN cana-2813 96 32 to to PART cana-2813 96 33 find find VERB cana-2813 96 34 the the DET cana-2813 96 35 gene gene NOUN cana-2813 96 36 subset subset VERB cana-2813 96 37 that that PRON cana-2813 96 38 maximizes maximize VERB cana-2813 96 39 classification classification NOUN cana-2813 96 40 accuracy accuracy NOUN cana-2813 96 41 : : PUNCT cana-2813 96 42 𝑓(𝑆 𝑓(𝑆 X cana-2813 96 43 ) ) PUNCT cana-2813 97 1 = = PUNCT cana-2813 97 2 π΄π‘π‘π‘’π‘Ÿπ‘Žπ‘π‘¦(πΆπ‘™π‘Žπ‘ π‘ π‘–π‘“π‘–π‘’π‘Ÿ(𝑆 π΄π‘π‘π‘’π‘Ÿπ‘Žπ‘π‘¦(πΆπ‘™π‘Žπ‘ π‘ π‘–π‘“π‘–π‘’π‘Ÿ(𝑆 PROPN cana-2813 97 3 ) ) PUNCT cana-2813 97 4 ) ) PUNCT cana-2813 97 5 equation equation NOUN cana-2813 97 6 3 3 NUM cana-2813 97 7 by by ADP cana-2813 97 8 evaluating evaluate VERB cana-2813 97 9 various various ADJ cana-2813 97 10 subsets subset NOUN cana-2813 97 11 of of ADP cana-2813 97 12 genes gene NOUN cana-2813 97 13 , , PUNCT cana-2813 97 14 mfo mfo PROPN cana-2813 97 15 identifies identify VERB cana-2813 97 16 those those PRON cana-2813 97 17 that that PRON cana-2813 97 18 are be AUX cana-2813 97 19 most most ADV cana-2813 97 20 significant significant ADJ cana-2813 97 21 for for ADP cana-2813 97 22 the the DET cana-2813 97 23 classification classification NOUN cana-2813 97 24 task task NOUN cana-2813 97 25 , , PUNCT cana-2813 97 26 thereby thereby ADV cana-2813 97 27 reducing reduce VERB cana-2813 97 28 dimensionality dimensionality NOUN cana-2813 97 29 and and CCONJ cana-2813 97 30 mitigating mitigate VERB cana-2813 97 31 issues issue NOUN cana-2813 97 32 related relate VERB cana-2813 97 33 to to ADP cana-2813 97 34 the the DET cana-2813 97 35 " " PUNCT cana-2813 97 36 curse curse NOUN cana-2813 97 37 of of ADP cana-2813 97 38 dimensionality dimensionality NOUN cana-2813 97 39 . . PUNCT cana-2813 97 40 " " PUNCT cana-2813 98 1 [ [ X cana-2813 98 2 27 27 NUM cana-2813 98 3 ] ] PUNCT cana-2813 98 4 secondly secondly ADV cana-2813 98 5 , , PUNCT cana-2813 98 6 hyperparameter hyperparameter NOUN cana-2813 98 7 optimization optimization NOUN cana-2813 98 8 is be AUX cana-2813 98 9 essential essential ADJ cana-2813 98 10 for for ADP cana-2813 98 11 fine fine ADV cana-2813 98 12 - - PUNCT cana-2813 98 13 tuning tune VERB cana-2813 98 14 deep deep ADJ cana-2813 98 15 learning learning NOUN cana-2813 98 16 models model NOUN cana-2813 98 17 like like ADP cana-2813 98 18 dnabert dnabert NOUN cana-2813 98 19 . . PUNCT cana-2813 99 1 hyperparameters hyperparameter NOUN cana-2813 99 2 such such ADJ cana-2813 99 3 as as ADP cana-2813 99 4 learning learn VERB cana-2813 99 5 rates rate NOUN cana-2813 99 6 , , PUNCT cana-2813 99 7 batch batch NOUN cana-2813 99 8 sizes size NOUN cana-2813 99 9 , , PUNCT cana-2813 99 10 and and CCONJ cana-2813 99 11 the the DET cana-2813 99 12 number number NOUN cana-2813 99 13 of of ADP cana-2813 99 14 epochs epoch NOUN cana-2813 99 15 need need VERB cana-2813 99 16 careful careful ADJ cana-2813 99 17 tuning tuning NOUN cana-2813 99 18 to to PART cana-2813 99 19 attain attain VERB cana-2813 99 20 optimal optimal ADJ cana-2813 99 21 performance performance NOUN cana-2813 99 22 . . PUNCT cana-2813 100 1 mfo mfo PROPN cana-2813 100 2 is be AUX cana-2813 100 3 utilized utilize VERB cana-2813 100 4 to to PART cana-2813 100 5 explore explore VERB cana-2813 100 6 the the DET cana-2813 100 7 hyperparameter hyperparameter NOUN cana-2813 100 8 space space NOUN cana-2813 100 9 and and CCONJ cana-2813 100 10 identify identify VERB cana-2813 100 11 the the DET cana-2813 100 12 settings setting NOUN cana-2813 100 13 that that PRON cana-2813 100 14 improve improve VERB cana-2813 100 15 the the DET cana-2813 100 16 model model NOUN cana-2813 100 17 's 's PART cana-2813 100 18 accuracy accuracy NOUN cana-2813 100 19 and and CCONJ cana-2813 100 20 generalization generalization NOUN cana-2813 100 21 . . PUNCT cana-2813 101 1 the the DET cana-2813 101 2 hyperparameter hyperparameter NOUN cana-2813 101 3 optimization optimization NOUN cana-2813 101 4 problem problem NOUN cana-2813 101 5 can can AUX cana-2813 101 6 be be AUX cana-2813 101 7 stated state VERB cana-2813 101 8 as as ADP cana-2813 101 9 minimize minimize VERB cana-2813 101 10 β€Š β€Š SPACE cana-2813 101 11 loss loss NOUN cana-2813 101 12 ( ( PUNCT cana-2813 101 13 h h NOUN cana-2813 101 14 ) ) PUNCT cana-2813 101 15 , , PUNCT cana-2813 101 16 where where SCONJ cana-2813 101 17 h h NOUN cana-2813 101 18 represents represent VERB cana-2813 101 19 the the DET cana-2813 101 20 set set NOUN cana-2813 101 21 of of ADP cana-2813 101 22 hyperparameters hyperparameter NOUN cana-2813 101 23 , , PUNCT cana-2813 101 24 and and CCONJ cana-2813 101 25 loss(h loss(h PROPN cana-2813 101 26 ) ) PUNCT cana-2813 101 27 is be AUX cana-2813 101 28 the the DET cana-2813 101 29 loss loss NOUN cana-2813 101 30 function function NOUN cana-2813 101 31 evaluated evaluate VERB cana-2813 101 32 on on ADP cana-2813 101 33 validation validation NOUN cana-2813 101 34 data datum NOUN cana-2813 102 1 [ [ X cana-2813 102 2 28 28 NUM cana-2813 102 3 ] ] PUNCT cana-2813 102 4 . . PUNCT cana-2813 103 1 mfo mfo PROPN cana-2813 103 2 ’s ’s PART cana-2813 103 3 ability ability NOUN cana-2813 103 4 to to PART cana-2813 103 5 efficiently efficiently ADV cana-2813 103 6 explore explore VERB cana-2813 103 7 and and CCONJ cana-2813 103 8 exploit exploit VERB cana-2813 103 9 the the DET cana-2813 103 10 hyperparameter hyperparameter NOUN cana-2813 103 11 space space NOUN cana-2813 103 12 ensures ensure VERB cana-2813 103 13 that that SCONJ cana-2813 103 14 dnabert dnabert PROPN cana-2813 103 15 operates operate VERB cana-2813 103 16 at at ADP cana-2813 103 17 its its PRON cana-2813 103 18 full full ADJ cana-2813 103 19 potential potential NOUN cana-2813 103 20 . . PUNCT cana-2813 104 1 after after ADP cana-2813 104 2 feature feature NOUN cana-2813 104 3 selection selection NOUN cana-2813 104 4 with with ADP cana-2813 104 5 mfo mfo PROPN cana-2813 104 6 , , PUNCT cana-2813 104 7 dnabert dnabert NOUN cana-2813 104 8 is be AUX cana-2813 104 9 fine fine ADV cana-2813 104 10 - - PUNCT cana-2813 104 11 tuned tune VERB cana-2813 104 12 on on ADP cana-2813 104 13 the the DET cana-2813 104 14 selected select VERB cana-2813 104 15 gene gene NOUN cana-2813 104 16 subset subset NOUN cana-2813 104 17 . . PUNCT cana-2813 105 1 dnabert dnabert PROPN cana-2813 105 2 's 's PART cana-2813 105 3 pretrained pretraine VERB cana-2813 105 4 embeddings embedding NOUN cana-2813 105 5 , , PUNCT cana-2813 105 6 which which PRON cana-2813 105 7 capture capture VERB cana-2813 105 8 contextual contextual ADJ cana-2813 105 9 relationships relationship NOUN cana-2813 105 10 between between ADP cana-2813 105 11 genes gene NOUN cana-2813 105 12 , , PUNCT cana-2813 105 13 are be AUX cana-2813 105 14 adapted adapt VERB cana-2813 105 15 to to ADP cana-2813 105 16 the the DET cana-2813 105 17 specific specific ADJ cana-2813 105 18 classification classification NOUN cana-2813 105 19 task task NOUN cana-2813 105 20 . . PUNCT cana-2813 106 1 the the DET cana-2813 106 2 model model NOUN cana-2813 106 3 is be AUX cana-2813 106 4 trained train VERB cana-2813 106 5 on on ADP cana-2813 106 6 the the DET cana-2813 106 7 refined refined ADJ cana-2813 106 8 feature feature NOUN cana-2813 106 9 set set NOUN cana-2813 106 10 , , PUNCT cana-2813 106 11 and and CCONJ cana-2813 106 12 its its PRON cana-2813 106 13 performance performance NOUN cana-2813 106 14 is be AUX cana-2813 106 15 communications communication NOUN cana-2813 106 16 on on ADP cana-2813 106 17 applied apply VERB cana-2813 106 18 nonlinear nonlinear ADJ cana-2813 106 19 analysis analysis NOUN cana-2813 106 20 issn issn NOUN cana-2813 106 21 : : PUNCT cana-2813 106 22 1074 1074 NUM cana-2813 106 23 - - PUNCT cana-2813 106 24 133x 133x NUM cana-2813 106 25 vol vol NOUN cana-2813 106 26 32 32 NUM cana-2813 106 27 no no NOUN cana-2813 106 28 . . PUNCT cana-2813 107 1 4s 4s NUM cana-2813 107 2 ( ( PUNCT cana-2813 107 3 2025 2025 NUM cana-2813 107 4 ) ) PUNCT cana-2813 107 5 275 275 NUM cana-2813 107 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 107 7 confirmed confirm VERB cana-2813 107 8 using use VERB cana-2813 107 9 metrics metric NOUN cana-2813 107 10 such such ADJ cana-2813 107 11 as as ADP cana-2813 107 12 accuracy accuracy NOUN cana-2813 107 13 , , PUNCT cana-2813 107 14 precision precision NOUN cana-2813 107 15 , , PUNCT cana-2813 107 16 recall recall NOUN cana-2813 107 17 , , PUNCT cana-2813 107 18 and and CCONJ cana-2813 107 19 f1 f1 NOUN cana-2813 107 20 - - PUNCT cana-2813 107 21 score score NOUN cana-2813 107 22 . . PUNCT cana-2813 108 1 validation validation NOUN cana-2813 108 2 on on ADP cana-2813 108 3 independent independent ADJ cana-2813 108 4 datasets dataset NOUN cana-2813 108 5 ensures ensure VERB cana-2813 108 6 the the DET cana-2813 108 7 robustness robustness NOUN cana-2813 108 8 and and CCONJ cana-2813 108 9 generalizability generalizability NOUN cana-2813 108 10 of of ADP cana-2813 108 11 the the DET cana-2813 108 12 approach approach NOUN cana-2813 108 13 . . PUNCT cana-2813 109 1 when when SCONJ cana-2813 109 2 integrating integrate VERB cana-2813 109 3 the the DET cana-2813 109 4 mayfly mayfly NOUN cana-2813 109 5 optimization optimization NOUN cana-2813 109 6 algorithm algorithm NOUN cana-2813 109 7 ( ( PUNCT cana-2813 109 8 mfo mfo PROPN cana-2813 109 9 ) ) PUNCT cana-2813 109 10 with with ADP cana-2813 109 11 dnabert dnabert NOUN cana-2813 109 12 for for ADP cana-2813 109 13 genomic genomic ADJ cana-2813 109 14 data datum NOUN cana-2813 109 15 analysis analysis NOUN cana-2813 109 16 , , PUNCT cana-2813 109 17 key key ADJ cana-2813 109 18 mfo mfo NOUN cana-2813 109 19 parameters parameter NOUN cana-2813 109 20 include include VERB cana-2813 109 21 the the DET cana-2813 109 22 number number NOUN cana-2813 109 23 of of ADP cana-2813 109 24 iterations iteration NOUN cana-2813 109 25 , , PUNCT cana-2813 109 26 population population NOUN cana-2813 109 27 size size NOUN cana-2813 109 28 , , PUNCT cana-2813 109 29 attraction attraction NOUN cana-2813 109 30 constants constant NOUN cana-2813 109 31 , , PUNCT cana-2813 109 32 social social ADJ cana-2813 109 33 factors factor NOUN cana-2813 109 34 , , PUNCT cana-2813 109 35 and and CCONJ cana-2813 109 36 inertia inertia NOUN cana-2813 109 37 coefficients coefficient NOUN cana-2813 109 38 . . PUNCT cana-2813 110 1 table table NOUN cana-2813 110 2 1 1 NUM cana-2813 110 3 shows show VERB cana-2813 110 4 the the DET cana-2813 110 5 parameters parameter NOUN cana-2813 110 6 used use VERB cana-2813 110 7 for for ADP cana-2813 110 8 mfo mfo PROPN cana-2813 110 9 application application NOUN cana-2813 110 10 . . PUNCT cana-2813 111 1 these these DET cana-2813 111 2 parameters parameter NOUN cana-2813 111 3 significantly significantly ADV cana-2813 111 4 influence influence VERB cana-2813 111 5 the the DET cana-2813 111 6 optimization optimization NOUN cana-2813 111 7 process process NOUN cana-2813 111 8 , , PUNCT cana-2813 111 9 ensuring ensure VERB cana-2813 111 10 efficient efficient ADJ cana-2813 111 11 feature feature NOUN cana-2813 111 12 selection selection NOUN cana-2813 111 13 and and CCONJ cana-2813 111 14 model model NOUN cana-2813 111 15 enhancement enhancement NOUN cana-2813 111 16 . . PUNCT cana-2813 112 1 table.1 table.1 VERB cana-2813 112 2 : : PUNCT cana-2813 112 3 parameters parameter NOUN cana-2813 112 4 used use VERB cana-2813 112 5 in in ADP cana-2813 112 6 mfo mfo PROPN cana-2813 112 7 applications application NOUN cana-2813 112 8 parameter parameter NOUN cana-2813 112 9 description description NOUN cana-2813 112 10 typical typical ADJ cana-2813 112 11 value value NOUN cana-2813 112 12 / / SYM cana-2813 112 13 range range NOUN cana-2813 112 14 number number NOUN cana-2813 112 15 of of ADP cana-2813 112 16 iterations iteration NOUN cana-2813 112 17 total total ADJ cana-2813 112 18 optimization optimization NOUN cana-2813 112 19 cycles cycle NOUN cana-2813 112 20 to to PART cana-2813 112 21 achieve achieve VERB cana-2813 112 22 convergence convergence NOUN cana-2813 112 23 100 100 NUM cana-2813 112 24 population population NOUN cana-2813 112 25 size size NOUN cana-2813 112 26 total total ADJ cana-2813 112 27 number number NOUN cana-2813 112 28 of of ADP cana-2813 112 29 candidate candidate NOUN cana-2813 112 30 solutions solution NOUN cana-2813 112 31 ( ( PUNCT cana-2813 112 32 mayflies mayfly NOUN cana-2813 112 33 ) ) PUNCT cana-2813 112 34 30 30 NUM cana-2813 112 35 attraction attraction NOUN cana-2813 112 36 constant constant ADJ cana-2813 112 37 1 1 NUM cana-2813 112 38 controls control NOUN cana-2813 112 39 influence influence NOUN cana-2813 112 40 of of ADP cana-2813 112 41 male male ADJ cana-2813 112 42 - - PUNCT cana-2813 112 43 female female ADJ cana-2813 112 44 attraction attraction NOUN cana-2813 112 45 1 1 NUM cana-2813 112 46 attraction attraction NOUN cana-2813 112 47 constant constant ADJ cana-2813 112 48 2 2 NUM cana-2813 112 49 controls control NOUN cana-2813 112 50 influence influence NOUN cana-2813 112 51 of of ADP cana-2813 112 52 male male ADJ cana-2813 112 53 - - PUNCT cana-2813 112 54 male male NOUN cana-2813 112 55 repulsion repulsion NOUN cana-2813 112 56 1 1 NUM cana-2813 112 57 social social ADJ cana-2813 112 58 factor factor NOUN cana-2813 112 59 balances balance VERB cana-2813 112 60 exploration exploration NOUN cana-2813 112 61 vs. vs. ADP cana-2813 112 62 exploitation exploitation NOUN cana-2813 112 63 1.5 1.5 NUM cana-2813 112 64 inertia inertia NOUN cana-2813 112 65 coefficient coefficient NOUN cana-2813 112 66 dampens dampen VERB cana-2813 112 67 movement movement NOUN cana-2813 112 68 over over ADP cana-2813 112 69 generations generation NOUN cana-2813 112 70 to to PART cana-2813 112 71 avoid avoid VERB cana-2813 112 72 stagnation stagnation NOUN cana-2813 112 73 0.8 0.8 NUM cana-2813 112 74 mutation mutation NOUN cana-2813 112 75 rate rate NOUN cana-2813 112 76 probability probability NOUN cana-2813 112 77 of of ADP cana-2813 112 78 random random ADJ cana-2813 112 79 change change NOUN cana-2813 112 80 to to PART cana-2813 112 81 enhance enhance VERB cana-2813 112 82 diversity diversity NOUN cana-2813 112 83 0.5 0.5 NUM cana-2813 112 84 in in ADP cana-2813 112 85 the the DET cana-2813 112 86 context context NOUN cana-2813 112 87 of of ADP cana-2813 112 88 dnabert dnabert ADJ cana-2813 112 89 integration integration NOUN cana-2813 112 90 , , PUNCT cana-2813 112 91 mfo mfo PROPN cana-2813 112 92 optimizes optimize VERB cana-2813 112 93 hyperparameters hyperparameter NOUN cana-2813 112 94 or or CCONJ cana-2813 112 95 selects select VERB cana-2813 112 96 relevant relevant ADJ cana-2813 112 97 features feature NOUN cana-2813 112 98 , , PUNCT cana-2813 112 99 such such ADJ cana-2813 112 100 as as ADP cana-2813 112 101 sequence sequence NOUN cana-2813 112 102 length length NOUN cana-2813 112 103 or or CCONJ cana-2813 112 104 k k NOUN cana-2813 112 105 - - PUNCT cana-2813 112 106 mer mer NOUN cana-2813 112 107 size size NOUN cana-2813 112 108 , , PUNCT cana-2813 112 109 for for ADP cana-2813 112 110 better well ADJ cana-2813 112 111 classification classification NOUN cana-2813 112 112 of of ADP cana-2813 112 113 genomic genomic ADJ cana-2813 112 114 sequences sequence NOUN cana-2813 112 115 . . PUNCT cana-2813 113 1 the the DET cana-2813 113 2 number number NOUN cana-2813 113 3 of of ADP cana-2813 113 4 iterations iteration NOUN cana-2813 113 5 and and CCONJ cana-2813 113 6 population population NOUN cana-2813 113 7 size size NOUN cana-2813 113 8 determine determine VERB cana-2813 113 9 the the DET cana-2813 113 10 computational computational ADJ cana-2813 113 11 complexity complexity NOUN cana-2813 113 12 and and CCONJ cana-2813 113 13 exploration exploration NOUN cana-2813 113 14 capacity capacity NOUN cana-2813 113 15 . . PUNCT cana-2813 114 1 attraction attraction NOUN cana-2813 114 2 constants constant NOUN cana-2813 114 3 govern govern VERB cana-2813 114 4 the the DET cana-2813 114 5 balance balance NOUN cana-2813 114 6 between between ADP cana-2813 114 7 convergence convergence NOUN cana-2813 114 8 speed speed NOUN cana-2813 114 9 and and CCONJ cana-2813 114 10 solution solution NOUN cana-2813 114 11 diversity diversity NOUN cana-2813 114 12 . . PUNCT cana-2813 115 1 the the DET cana-2813 115 2 social social ADJ cana-2813 115 3 factor factor NOUN cana-2813 115 4 enhances enhance VERB cana-2813 115 5 adaptability adaptability NOUN cana-2813 115 6 , , PUNCT cana-2813 115 7 while while SCONJ cana-2813 115 8 the the DET cana-2813 115 9 inertia inertia NOUN cana-2813 115 10 coefficient coefficient NOUN cana-2813 115 11 prevents prevent VERB cana-2813 115 12 premature premature ADJ cana-2813 115 13 convergence convergence NOUN cana-2813 115 14 by by ADP cana-2813 115 15 maintaining maintain VERB cana-2813 115 16 diversity diversity NOUN cana-2813 115 17 in in ADP cana-2813 115 18 mayfly mayfly NOUN cana-2813 115 19 velocities velocity NOUN cana-2813 115 20 . . PUNCT cana-2813 116 1 adjusting adjust VERB cana-2813 116 2 the the DET cana-2813 116 3 mutation mutation NOUN cana-2813 116 4 rate rate NOUN cana-2813 116 5 ensures ensure VERB cana-2813 116 6 innovative innovative ADJ cana-2813 116 7 exploration exploration NOUN cana-2813 116 8 of of ADP cana-2813 116 9 the the DET cana-2813 116 10 solution solution NOUN cana-2813 116 11 space space NOUN cana-2813 116 12 , , PUNCT cana-2813 116 13 which which PRON cana-2813 116 14 is be AUX cana-2813 116 15 crucial crucial ADJ cana-2813 116 16 for for ADP cana-2813 116 17 dnabert dnabert PROPN cana-2813 116 18 ’s ’s PART cana-2813 116 19 high high ADJ cana-2813 116 20 - - PUNCT cana-2813 116 21 dimensional dimensional ADJ cana-2813 116 22 genomic genomic NOUN cana-2813 116 23 representations representation NOUN cana-2813 116 24 . . PUNCT cana-2813 117 1 these these DET cana-2813 117 2 parameters parameter NOUN cana-2813 117 3 are be AUX cana-2813 117 4 typically typically ADV cana-2813 117 5 fine fine ADV cana-2813 117 6 - - PUNCT cana-2813 117 7 tuned tune VERB cana-2813 117 8 based base VERB cana-2813 117 9 on on ADP cana-2813 117 10 experimental experimental ADJ cana-2813 117 11 results result NOUN cana-2813 117 12 to to PART cana-2813 117 13 attain attain VERB cana-2813 117 14 the the DET cana-2813 117 15 best good ADJ cana-2813 117 16 trade trade NOUN cana-2813 117 17 - - PUNCT cana-2813 117 18 off off NOUN cana-2813 117 19 between between ADP cana-2813 117 20 performance performance NOUN cana-2813 117 21 and and CCONJ cana-2813 117 22 computational computational ADJ cana-2813 117 23 efficiency efficiency NOUN cana-2813 117 24 for for ADP cana-2813 117 25 genomic genomic ADJ cana-2813 117 26 classification classification NOUN cana-2813 117 27 tasks task NOUN cana-2813 117 28 . . PUNCT cana-2813 118 1 the the DET cana-2813 118 2 mayfly mayfly NOUN cana-2813 118 3 optimization optimization NOUN cana-2813 118 4 algorithm algorithm NOUN cana-2813 118 5 ( ( PUNCT cana-2813 118 6 mfo mfo PROPN cana-2813 118 7 ) ) PUNCT cana-2813 118 8 , , PUNCT cana-2813 118 9 when when SCONJ cana-2813 118 10 integrated integrate VERB cana-2813 118 11 with with ADP cana-2813 118 12 dnabert dnabert NOUN cana-2813 118 13 , , PUNCT cana-2813 118 14 employs employ VERB cana-2813 118 15 a a DET cana-2813 118 16 population population NOUN cana-2813 118 17 - - PUNCT cana-2813 118 18 based base VERB cana-2813 118 19 feature feature NOUN cana-2813 118 20 selection selection NOUN cana-2813 118 21 method method NOUN cana-2813 118 22 tailored tailor VERB cana-2813 118 23 to to PART cana-2813 118 24 optimize optimize VERB cana-2813 118 25 subsets subset NOUN cana-2813 118 26 of of ADP cana-2813 118 27 features feature NOUN cana-2813 118 28 ( ( PUNCT cana-2813 118 29 genes gene NOUN cana-2813 118 30 or or CCONJ cana-2813 118 31 sequences sequence NOUN cana-2813 118 32 ) ) PUNCT cana-2813 118 33 that that PRON cana-2813 118 34 contribute contribute VERB cana-2813 118 35 most most ADV cana-2813 118 36 significantly significantly ADV cana-2813 118 37 to to ADP cana-2813 118 38 classification classification NOUN cana-2813 118 39 performance performance NOUN cana-2813 118 40 . . PUNCT cana-2813 119 1 figure figure NOUN cana-2813 119 2 2 2 NUM cana-2813 119 3 shows show VERB cana-2813 119 4 the the DET cana-2813 119 5 feature feature NOUN cana-2813 119 6 selection selection NOUN cana-2813 119 7 mechanisms mechanism NOUN cana-2813 119 8 of of ADP cana-2813 119 9 mfo mfo PROPN cana-2813 119 10 . . PUNCT cana-2813 120 1 in in ADP cana-2813 120 2 the the DET cana-2813 120 3 genomic genomic ADJ cana-2813 120 4 data datum NOUN cana-2813 120 5 context context NOUN cana-2813 120 6 , , PUNCT cana-2813 120 7 this this DET cana-2813 120 8 process process NOUN cana-2813 120 9 enhances enhance VERB cana-2813 120 10 the the DET cana-2813 120 11 interpretability interpretability NOUN cana-2813 120 12 of of ADP cana-2813 120 13 dnabert dnabert NOUN cana-2813 120 14 's 's PART cana-2813 120 15 output output NOUN cana-2813 120 16 by by ADP cana-2813 120 17 reducing reduce VERB cana-2813 120 18 the the DET cana-2813 120 19 dimensionality dimensionality NOUN cana-2813 120 20 of of ADP cana-2813 120 21 input input NOUN cana-2813 120 22 data datum NOUN cana-2813 120 23 , , PUNCT cana-2813 120 24 improving improve VERB cana-2813 120 25 computational computational ADJ cana-2813 120 26 efficiency efficiency NOUN cana-2813 120 27 , , PUNCT cana-2813 120 28 and and CCONJ cana-2813 120 29 focusing focus VERB cana-2813 120 30 on on ADP cana-2813 120 31 the the DET cana-2813 120 32 most most ADV cana-2813 120 33 biologically biologically ADV cana-2813 120 34 relevant relevant ADJ cana-2813 120 35 features feature NOUN cana-2813 120 36 . . PUNCT cana-2813 121 1 communications communication NOUN cana-2813 121 2 on on ADP cana-2813 121 3 applied apply VERB cana-2813 121 4 nonlinear nonlinear ADJ cana-2813 121 5 analysis analysis NOUN cana-2813 121 6 issn issn NOUN cana-2813 121 7 : : PUNCT cana-2813 121 8 1074 1074 NUM cana-2813 121 9 - - PUNCT cana-2813 121 10 133x 133x NUM cana-2813 121 11 vol vol NOUN cana-2813 121 12 32 32 NUM cana-2813 121 13 no no NOUN cana-2813 121 14 . . PUNCT cana-2813 122 1 4s 4s NUM cana-2813 122 2 ( ( PUNCT cana-2813 122 3 2025 2025 NUM cana-2813 122 4 ) ) PUNCT cana-2813 122 5 276 276 NUM cana-2813 123 1 https://internationalpubls.com https://internationalpubls.com X cana-2813 123 2 fig.2 fig.2 PROPN cana-2813 123 3 : : PUNCT cana-2813 123 4 feature feature NOUN cana-2813 123 5 selection selection NOUN cana-2813 123 6 mechanism mechanism NOUN cana-2813 123 7 in in ADP cana-2813 123 8 mfo mfo PROPN cana-2813 123 9 when when SCONJ cana-2813 123 10 paired pair VERB cana-2813 123 11 with with ADP cana-2813 123 12 dnabert dnabert NOUN cana-2813 123 13 , , PUNCT cana-2813 123 14 it it PRON cana-2813 123 15 processes process VERB cana-2813 123 16 genomic genomic ADJ cana-2813 123 17 sequences sequence NOUN cana-2813 123 18 , , PUNCT cana-2813 123 19 and and CCONJ cana-2813 123 20 mfo mfo NOUN cana-2813 123 21 optimizes optimize VERB cana-2813 123 22 the the DET cana-2813 123 23 selection selection NOUN cana-2813 123 24 of of ADP cana-2813 123 25 input input NOUN cana-2813 123 26 sequences sequence NOUN cana-2813 123 27 or or CCONJ cana-2813 123 28 derived derive VERB cana-2813 123 29 k k ADJ cana-2813 123 30 - - PUNCT cana-2813 123 31 mer mer NOUN cana-2813 123 32 embeddings embedding NOUN cana-2813 123 33 . . PUNCT cana-2813 124 1 the the DET cana-2813 124 2 classification classification NOUN cana-2813 124 3 performance performance NOUN cana-2813 124 4 of of ADP cana-2813 124 5 dnabert dnabert ADJ cana-2813 124 6 guides guide NOUN cana-2813 124 7 the the DET cana-2813 124 8 fitness fitness NOUN cana-2813 124 9 evaluation evaluation NOUN cana-2813 124 10 in in ADP cana-2813 124 11 mfo mfo PROPN cana-2813 124 12 , , PUNCT cana-2813 124 13 forming form VERB cana-2813 124 14 a a DET cana-2813 124 15 feedback feedback NOUN cana-2813 124 16 loop loop NOUN cana-2813 124 17 for for ADP cana-2813 124 18 dynamic dynamic ADJ cana-2813 124 19 feature feature NOUN cana-2813 124 20 selection selection NOUN cana-2813 124 21 . . PUNCT cana-2813 125 1 by by ADP cana-2813 125 2 identifying identify VERB cana-2813 125 3 the the DET cana-2813 125 4 most most ADV cana-2813 125 5 informative informative ADJ cana-2813 125 6 sequences sequence NOUN cana-2813 125 7 , , PUNCT cana-2813 125 8 mfo mfo PROPN cana-2813 125 9 minimizes minimize VERB cana-2813 125 10 redundant redundant ADJ cana-2813 125 11 or or CCONJ cana-2813 125 12 irrelevant irrelevant ADJ cana-2813 125 13 inputs input NOUN cana-2813 125 14 , , PUNCT cana-2813 125 15 allowing allow VERB cana-2813 125 16 dnabert dnabert NOUN cana-2813 125 17 to to PART cana-2813 125 18 focus focus VERB cana-2813 125 19 on on ADP cana-2813 125 20 high high ADJ cana-2813 125 21 - - PUNCT cana-2813 125 22 quality quality NOUN cana-2813 125 23 data datum NOUN cana-2813 125 24 for for ADP cana-2813 125 25 improved improved ADJ cana-2813 125 26 performance performance NOUN cana-2813 125 27 . . PUNCT cana-2813 126 1 this this DET cana-2813 126 2 integrated integrate VERB cana-2813 126 3 approach approach NOUN cana-2813 126 4 leverages leverage VERB cana-2813 126 5 mfo mfo PROPN cana-2813 126 6 's 's PART cana-2813 126 7 robust robust ADJ cana-2813 126 8 global global ADJ cana-2813 126 9 search search NOUN cana-2813 126 10 capabilities capability NOUN cana-2813 126 11 and and CCONJ cana-2813 126 12 dnabert dnabert NOUN cana-2813 126 13 's 's PART cana-2813 126 14 high high ADJ cana-2813 126 15 - - PUNCT cana-2813 126 16 resolution resolution NOUN cana-2813 126 17 feature feature NOUN cana-2813 126 18 encoding encoding NOUN cana-2813 126 19 to to PART cana-2813 126 20 optimize optimize VERB cana-2813 126 21 genomic genomic ADJ cana-2813 126 22 data datum NOUN cana-2813 126 23 analysis analysis NOUN cana-2813 126 24 effectively effectively ADV cana-2813 126 25 . . PUNCT cana-2813 127 1 the the DET cana-2813 127 2 resulting result VERB cana-2813 127 3 framework framework NOUN cana-2813 127 4 is be AUX cana-2813 127 5 not not PART cana-2813 127 6 only only ADV cana-2813 127 7 computationally computationally ADV cana-2813 127 8 efficient efficient ADJ cana-2813 127 9 but but CCONJ cana-2813 127 10 also also ADV cana-2813 127 11 enhances enhance VERB cana-2813 127 12 the the DET cana-2813 127 13 interpretability interpretability NOUN cana-2813 127 14 and and CCONJ cana-2813 127 15 accuracy accuracy NOUN cana-2813 127 16 of of ADP cana-2813 127 17 classification classification NOUN cana-2813 127 18 in in ADP cana-2813 127 19 genomic genomic ADJ cana-2813 127 20 studies study NOUN cana-2813 127 21 . . PUNCT cana-2813 128 1 integrating integrate VERB cana-2813 128 2 mfo mfo PROPN cana-2813 128 3 with with ADP cana-2813 128 4 dnabert dnabert PROPN cana-2813 128 5 offers offer VERB cana-2813 128 6 several several ADJ cana-2813 128 7 significant significant ADJ cana-2813 128 8 advantages advantage NOUN cana-2813 128 9 . . PUNCT cana-2813 129 1 firstly firstly ADV cana-2813 129 2 , , PUNCT cana-2813 129 3 it it PRON cana-2813 129 4 improves improve VERB cana-2813 129 5 classification classification NOUN cana-2813 129 6 accuracy accuracy NOUN cana-2813 129 7 by by ADP cana-2813 129 8 selecting select VERB cana-2813 129 9 the the DET cana-2813 129 10 most most ADV cana-2813 129 11 relevant relevant ADJ cana-2813 129 12 gene gene NOUN cana-2813 129 13 features feature NOUN cana-2813 129 14 and and CCONJ cana-2813 129 15 optimizing optimize VERB cana-2813 129 16 model model NOUN cana-2813 129 17 parameters parameter NOUN cana-2813 129 18 . . PUNCT cana-2813 130 1 this this DET cana-2813 130 2 integration integration NOUN cana-2813 130 3 addresses address VERB cana-2813 130 4 the the DET cana-2813 130 5 challenge challenge NOUN cana-2813 130 6 of of ADP cana-2813 130 7 high high ADJ cana-2813 130 8 - - PUNCT cana-2813 130 9 dimensional dimensional ADJ cana-2813 130 10 data datum NOUN cana-2813 130 11 by by ADP cana-2813 130 12 reducing reduce VERB cana-2813 130 13 dimensionality dimensionality NOUN cana-2813 130 14 and and CCONJ cana-2813 130 15 enhancing enhance VERB cana-2813 130 16 computational computational ADJ cana-2813 130 17 efficiency efficiency NOUN cana-2813 130 18 . . PUNCT cana-2813 131 1 secondly secondly ADV cana-2813 131 2 , , PUNCT cana-2813 131 3 optimizing optimize VERB cana-2813 131 4 hyperparameters hyperparameter NOUN cana-2813 131 5 with with ADP cana-2813 131 6 mfo mfo PROPN cana-2813 131 7 ensures ensure VERB cana-2813 131 8 that that SCONJ cana-2813 131 9 dnabert dnabert PROPN cana-2813 131 10 operates operate VERB cana-2813 131 11 with with ADP cana-2813 131 12 the the DET cana-2813 131 13 best good ADJ cana-2813 131 14 possible possible ADJ cana-2813 131 15 settings setting NOUN cana-2813 131 16 , , PUNCT cana-2813 131 17 leading lead VERB cana-2813 131 18 to to ADP cana-2813 131 19 more more ADV cana-2813 131 20 reliable reliable ADJ cana-2813 131 21 and and CCONJ cana-2813 131 22 precise precise ADJ cana-2813 131 23 classification classification NOUN cana-2813 131 24 results result NOUN cana-2813 131 25 . . PUNCT cana-2813 132 1 2.2 2.2 NUM cana-2813 132 2 . . PUNCT cana-2813 133 1 data datum NOUN cana-2813 133 2 collection collection NOUN cana-2813 133 3 the the DET cana-2813 133 4 data data NOUN cana-2813 133 5 collection collection NOUN cana-2813 133 6 process process NOUN cana-2813 133 7 for for ADP cana-2813 133 8 microarray microarray NOUN cana-2813 133 9 gene gene NOUN cana-2813 133 10 expression expression NOUN cana-2813 133 11 classification classification NOUN cana-2813 133 12 involved involve VERB cana-2813 133 13 a a DET cana-2813 133 14 series series NOUN cana-2813 133 15 of of ADP cana-2813 133 16 systematic systematic ADJ cana-2813 133 17 steps step NOUN cana-2813 133 18 to to PART cana-2813 133 19 ensure ensure VERB cana-2813 133 20 the the DET cana-2813 133 21 acquisition acquisition NOUN cana-2813 133 22 of of ADP cana-2813 133 23 high high ADJ cana-2813 133 24 - - PUNCT cana-2813 133 25 quality quality NOUN cana-2813 133 26 , , PUNCT cana-2813 133 27 labeled label VERB cana-2813 133 28 datasets dataset NOUN cana-2813 133 29 suitable suitable ADJ cana-2813 133 30 for for ADP cana-2813 133 31 training training NOUN cana-2813 133 32 and and CCONJ cana-2813 133 33 assessing assess VERB cana-2813 133 34 machine machine NOUN cana-2813 133 35 learning learning NOUN cana-2813 133 36 models model NOUN cana-2813 133 37 . . PUNCT cana-2813 134 1 the the DET cana-2813 134 2 dataset dataset NOUN cana-2813 134 3 available available ADJ cana-2813 134 4 in in ADP cana-2813 134 5 [ [ X cana-2813 134 6 32 32 NUM cana-2813 134 7 ] ] PUNCT cana-2813 134 8 , , PUNCT cana-2813 134 9 hosted host VERB cana-2813 134 10 by by ADP cana-2813 134 11 the the DET cana-2813 134 12 center center NOUN cana-2813 134 13 for for ADP cana-2813 134 14 systems system NOUN cana-2813 134 15 and and CCONJ cana-2813 134 16 synthetic synthetic ADJ cana-2813 134 17 biology biology NOUN cana-2813 134 18 at at ADP cana-2813 134 19 shenzhen shenzhen PROPN cana-2813 134 20 university university PROPN cana-2813 134 21 , , PUNCT cana-2813 134 22 encompasses encompass VERB cana-2813 134 23 various various ADJ cana-2813 134 24 collections collection NOUN cana-2813 134 25 for for ADP cana-2813 134 26 biomedical biomedical ADJ cana-2813 134 27 research research NOUN cana-2813 134 28 . . PUNCT cana-2813 135 1 microarray microarray NOUN cana-2813 135 2 gene gene NOUN cana-2813 135 3 expression expression NOUN cana-2813 135 4 image image NOUN cana-2813 135 5 data datum NOUN cana-2813 135 6 are be AUX cana-2813 135 7 taken take VERB cana-2813 135 8 from from ADP cana-2813 135 9 this this DET cana-2813 135 10 [ [ X cana-2813 135 11 32 32 NUM cana-2813 135 12 ] ] SYM cana-2813 135 13 repository repository NOUN cana-2813 135 14 for for ADP cana-2813 135 15 this this DET cana-2813 135 16 research research NOUN cana-2813 135 17 . . PUNCT cana-2813 136 1 the the DET cana-2813 136 2 summary summary NOUN cana-2813 136 3 of of ADP cana-2813 136 4 the the DET cana-2813 136 5 collected collect VERB cana-2813 136 6 data data NOUN cana-2813 136 7 is be AUX cana-2813 136 8 shown show VERB cana-2813 136 9 in in ADP cana-2813 136 10 table table NOUN cana-2813 136 11 2 2 NUM cana-2813 136 12 and and CCONJ cana-2813 136 13 table table NOUN cana-2813 136 14 3 3 NUM cana-2813 136 15 . . PUNCT cana-2813 137 1 also also ADV cana-2813 137 2 , , PUNCT cana-2813 137 3 the the DET cana-2813 137 4 same same ADJ cana-2813 137 5 images image NOUN cana-2813 137 6 of of ADP cana-2813 137 7 the the DET cana-2813 137 8 microarray microarray NOUN cana-2813 137 9 gene gene NOUN cana-2813 137 10 expression expression NOUN cana-2813 137 11 image image NOUN cana-2813 137 12 is be AUX cana-2813 137 13 shown show VERB cana-2813 137 14 in in ADP cana-2813 137 15 figure figure NOUN cana-2813 137 16 3 3 NUM cana-2813 137 17 . . PUNCT cana-2813 137 18 communications communication NOUN cana-2813 137 19 on on ADP cana-2813 137 20 applied apply VERB cana-2813 137 21 nonlinear nonlinear ADJ cana-2813 137 22 analysis analysis NOUN cana-2813 137 23 issn issn NOUN cana-2813 137 24 : : PUNCT cana-2813 137 25 1074 1074 NUM cana-2813 137 26 - - PUNCT cana-2813 137 27 133x 133x NUM cana-2813 137 28 vol vol NOUN cana-2813 137 29 32 32 NUM cana-2813 137 30 no no NOUN cana-2813 137 31 . . PUNCT cana-2813 138 1 4s 4s NUM cana-2813 138 2 ( ( PUNCT cana-2813 138 3 2025 2025 NUM cana-2813 138 4 ) ) PUNCT cana-2813 138 5 277 277 NUM cana-2813 138 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 138 7 table.2 table.2 PROPN cana-2813 138 8 : : PUNCT cana-2813 138 9 summary summary NOUN cana-2813 138 10 gene gene NOUN cana-2813 138 11 expression expression NOUN cana-2813 138 12 data datum NOUN cana-2813 138 13 with with ADP cana-2813 138 14 number number NOUN cana-2813 138 15 of of ADP cana-2813 138 16 classes class NOUN cana-2813 138 17 and and CCONJ cana-2813 138 18 instances instance VERB cana-2813 138 19 details detail NOUN cana-2813 138 20 descriptions description NOUN cana-2813 138 21 breast breast NOUN cana-2813 138 22 cancer cancer NOUN cana-2813 138 23 colon colon NOUN cana-2813 138 24 cancer cancer NOUN cana-2813 138 25 lung lung NOUN cana-2813 138 26 cancer cancer NOUN cana-2813 138 27 ovarian ovarian ADJ cana-2813 138 28 cancer cancer NOUN cana-2813 138 29 lymphom lymphom VERB cana-2813 138 30 a a DET cana-2813 138 31 no no NOUN cana-2813 138 32 . . PUNCT cana-2813 138 33 of of ADP cana-2813 138 34 instances instance NOUN cana-2813 138 35 97 97 NUM cana-2813 138 36 62 62 NUM cana-2813 138 37 203 203 NUM cana-2813 138 38 253 253 NUM cana-2813 138 39 66 66 NUM cana-2813 138 40 no no NOUN cana-2813 138 41 . . PUNCT cana-2813 139 1 of of ADP cana-2813 139 2 classes class NOUN cana-2813 139 3 2 2 NUM cana-2813 139 4 2 2 NUM cana-2813 139 5 5 5 NUM cana-2813 139 6 2 2 NUM cana-2813 139 7 3 3 NUM cana-2813 139 8 class class NOUN cana-2813 139 9 1 1 NUM cana-2813 139 10 46 46 NUM cana-2813 139 11 22 22 NUM cana-2813 139 12 139 139 NUM cana-2813 139 13 162 162 NUM cana-2813 139 14 46 46 NUM cana-2813 139 15 class class NOUN cana-2813 139 16 2 2 NUM cana-2813 139 17 51 51 NUM cana-2813 139 18 40 40 NUM cana-2813 139 19 17 17 NUM cana-2813 139 20 91 91 NUM cana-2813 139 21 9 9 NUM cana-2813 139 22 class class NOUN cana-2813 140 1 3 3 NUM cana-2813 140 2 6 6 NUM cana-2813 140 3 11 11 NUM cana-2813 140 4 class class NOUN cana-2813 140 5 4 4 NUM cana-2813 140 6 21 21 NUM cana-2813 140 7 class class NOUN cana-2813 140 8 5 5 NUM cana-2813 140 9 20 20 NUM cana-2813 140 10 table.3 table.3 PROPN cana-2813 140 11 : : PUNCT cana-2813 140 12 gene gene NOUN cana-2813 140 13 expression expression NOUN cana-2813 140 14 data datum NOUN cana-2813 140 15 mentioning mention VERB cana-2813 140 16 the the DET cana-2813 140 17 class class NOUN cana-2813 140 18 names name NOUN cana-2813 140 19 no no PROPN cana-2813 140 20 of of ADP cana-2813 140 21 classes class NOUN cana-2813 140 22 class class NOUN cana-2813 140 23 names name NOUN cana-2813 140 24 ( ( PUNCT cana-2813 140 25 no no INTJ cana-2813 140 26 . . NOUN cana-2813 140 27 of of ADP cana-2813 140 28 instances instance NOUN cana-2813 140 29 ) ) PUNCT cana-2813 140 30 breast breast NOUN cana-2813 140 31 cancer cancer NOUN cana-2813 140 32 2 2 NUM cana-2813 140 33 relapse relapse NOUN cana-2813 140 34 ( ( PUNCT cana-2813 140 35 46 46 NUM cana-2813 140 36 ) ) PUNCT cana-2813 140 37 non non ADJ cana-2813 140 38 - - NOUN cana-2813 140 39 relapse relapse ADJ cana-2813 140 40 ( ( PUNCT cana-2813 140 41 51 51 NUM cana-2813 140 42 ) ) PUNCT cana-2813 140 43 colon colon NOUN cana-2813 140 44 cancer cancer NOUN cana-2813 140 45 2 2 NUM cana-2813 140 46 normal normal ADJ cana-2813 140 47 ( ( PUNCT cana-2813 140 48 22 22 NUM cana-2813 140 49 ) ) PUNCT cana-2813 140 50 abnormal abnormal ADJ cana-2813 140 51 ( ( PUNCT cana-2813 140 52 40 40 NUM cana-2813 140 53 ) ) PUNCT cana-2813 140 54 lung lung NOUN cana-2813 140 55 cancer cancer NOUN cana-2813 140 56 5 5 NUM cana-2813 140 57 adenocarcin adenocarcin ADP cana-2813 140 58 omas oma NOUN cana-2813 140 59 ( ( PUNCT cana-2813 140 60 139 139 NUM cana-2813 140 61 ) ) PUNCT cana-2813 140 62 small small ADJ cana-2813 140 63 cell cell NOUN cana-2813 140 64 lung lung NOUN cana-2813 140 65 carcinomas carcinoma NOUN cana-2813 140 66 ( ( PUNCT cana-2813 140 67 17 17 NUM cana-2813 140 68 ) ) PUNCT cana-2813 140 69 squamous squamous ADJ cana-2813 140 70 cell cell NOUN cana-2813 140 71 carcinomas carcinoma NOUN cana-2813 140 72 ( ( PUNCT cana-2813 140 73 6 6 NUM cana-2813 140 74 ) ) PUNCT cana-2813 140 75 carcinoi carcinoi ADJ cana-2813 140 76 ds ds X cana-2813 140 77 ( ( PUNCT cana-2813 140 78 21 21 NUM cana-2813 140 79 ) ) PUNCT cana-2813 140 80 normal normal ADJ cana-2813 140 81 lung lung NOUN cana-2813 140 82 ( ( PUNCT cana-2813 140 83 20 20 NUM cana-2813 140 84 ) ) PUNCT cana-2813 140 85 ovarian ovarian ADJ cana-2813 140 86 cancer cancer NOUN cana-2813 140 87 2 2 NUM cana-2813 140 88 cancer cancer NOUN cana-2813 140 89 ( ( PUNCT cana-2813 140 90 162 162 NUM cana-2813 140 91 ) ) PUNCT cana-2813 140 92 normal normal ADJ cana-2813 140 93 ( ( PUNCT cana-2813 140 94 91 91 NUM cana-2813 140 95 ) ) PUNCT cana-2813 140 96 lympho lympho VERB cana-2813 140 97 ma ma PROPN cana-2813 140 98 3 3 NUM cana-2813 140 99 early early ADV cana-2813 140 100 ( ( PUNCT cana-2813 140 101 46 46 NUM cana-2813 140 102 ) ) PUNCT cana-2813 140 103 mid mid NOUN cana-2813 140 104 ( ( PUNCT cana-2813 140 105 9 9 NUM cana-2813 140 106 ) ) PUNCT cana-2813 140 107 late late ADV cana-2813 140 108 ( ( PUNCT cana-2813 140 109 11 11 NUM cana-2813 140 110 ) ) PUNCT cana-2813 140 111 fig.3 fig.3 PROPN cana-2813 140 112 : : PUNCT cana-2813 140 113 sample sample NOUN cana-2813 140 114 image image NOUN cana-2813 140 115 of of ADP cana-2813 140 116 the the DET cana-2813 140 117 gene gene NOUN cana-2813 140 118 expression expression NOUN cana-2813 140 119 microarray microarray NOUN cana-2813 140 120 of of ADP cana-2813 140 121 colon colon NOUN cana-2813 140 122 cancer cancer NOUN cana-2813 140 123 communications communication NOUN cana-2813 140 124 on on ADP cana-2813 140 125 applied apply VERB cana-2813 140 126 nonlinear nonlinear ADJ cana-2813 140 127 analysis analysis NOUN cana-2813 140 128 issn issn NOUN cana-2813 140 129 : : PUNCT cana-2813 140 130 1074 1074 NUM cana-2813 140 131 - - PUNCT cana-2813 140 132 133x 133x NUM cana-2813 140 133 vol vol NOUN cana-2813 140 134 32 32 NUM cana-2813 140 135 no no NOUN cana-2813 140 136 . . PUNCT cana-2813 141 1 4s 4s NUM cana-2813 141 2 ( ( PUNCT cana-2813 141 3 2025 2025 NUM cana-2813 141 4 ) ) PUNCT cana-2813 141 5 278 278 NUM cana-2813 141 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 141 7 figure figure NOUN cana-2813 141 8 4 4 NUM cana-2813 141 9 shows show VERB cana-2813 141 10 the the DET cana-2813 141 11 data datum NOUN cana-2813 141 12 collection collection NOUN cana-2813 141 13 process process NOUN cana-2813 141 14 for for ADP cana-2813 141 15 microarray microarray NOUN cana-2813 141 16 gene gene NOUN cana-2813 141 17 expression expression NOUN cana-2813 141 18 classification classification NOUN cana-2813 141 19 . . PUNCT cana-2813 142 1 the the DET cana-2813 142 2 selection selection NOUN cana-2813 142 3 process process NOUN cana-2813 142 4 emphasized emphasize VERB cana-2813 142 5 datasets dataset NOUN cana-2813 142 6 related relate VERB cana-2813 142 7 to to ADP cana-2813 142 8 particular particular ADJ cana-2813 142 9 types type NOUN cana-2813 142 10 of of ADP cana-2813 142 11 cancer cancer NOUN cana-2813 142 12 or or CCONJ cana-2813 142 13 diseases disease NOUN cana-2813 142 14 relevant relevant ADJ cana-2813 142 15 to to ADP cana-2813 142 16 the the DET cana-2813 142 17 study study NOUN cana-2813 142 18 . . PUNCT cana-2813 143 1 key key ADJ cana-2813 143 2 considerations consideration NOUN cana-2813 143 3 included include VERB cana-2813 143 4 the the DET cana-2813 143 5 focus focus NOUN cana-2813 143 6 on on ADP cana-2813 143 7 disease disease NOUN cana-2813 143 8 - - PUNCT cana-2813 143 9 specific specific ADJ cana-2813 143 10 datasets dataset NOUN cana-2813 143 11 , , PUNCT cana-2813 143 12 the the DET cana-2813 143 13 size size NOUN cana-2813 143 14 of of ADP cana-2813 143 15 the the DET cana-2813 143 16 samples sample NOUN cana-2813 143 17 , , PUNCT cana-2813 143 18 and and CCONJ cana-2813 143 19 the the DET cana-2813 143 20 overall overall ADJ cana-2813 143 21 quality quality NOUN cana-2813 143 22 of of ADP cana-2813 143 23 the the DET cana-2813 143 24 data datum NOUN cana-2813 143 25 . . PUNCT cana-2813 144 1 the the DET cana-2813 144 2 sample sample NOUN cana-2813 144 3 size size NOUN cana-2813 144 4 was be AUX cana-2813 144 5 particularly particularly ADV cana-2813 144 6 critical critical ADJ cana-2813 144 7 to to PART cana-2813 144 8 ensure ensure VERB cana-2813 144 9 that that SCONJ cana-2813 144 10 the the DET cana-2813 144 11 dataset dataset NOUN cana-2813 144 12 was be AUX cana-2813 144 13 large large ADJ cana-2813 144 14 enough enough ADV cana-2813 144 15 to to PART cana-2813 144 16 train train VERB cana-2813 144 17 and and CCONJ cana-2813 144 18 validate validate VERB cana-2813 144 19 the the DET cana-2813 144 20 machine machine NOUN cana-2813 144 21 learning learning NOUN cana-2813 144 22 models model NOUN cana-2813 144 23 effectively effectively ADV cana-2813 144 24 . . PUNCT cana-2813 145 1 additionally additionally ADV cana-2813 145 2 , , PUNCT cana-2813 145 3 datasets dataset NOUN cana-2813 145 4 with with ADP cana-2813 145 5 well well ADV cana-2813 145 6 - - PUNCT cana-2813 145 7 annotated annotate VERB cana-2813 145 8 metadata metadata NOUN cana-2813 145 9 , , PUNCT cana-2813 145 10 including include VERB cana-2813 145 11 patient patient ADJ cana-2813 145 12 demographics demographic NOUN cana-2813 145 13 , , PUNCT cana-2813 145 14 disease disease NOUN cana-2813 145 15 stages stage NOUN cana-2813 145 16 , , PUNCT cana-2813 145 17 and and CCONJ cana-2813 145 18 treatment treatment NOUN cana-2813 145 19 outcomes outcome NOUN cana-2813 145 20 , , PUNCT cana-2813 145 21 were be AUX cana-2813 145 22 prioritized prioritize VERB cana-2813 145 23 for for ADP cana-2813 145 24 their their PRON cana-2813 145 25 potential potential NOUN cana-2813 145 26 to to PART cana-2813 145 27 add add VERB cana-2813 145 28 depth depth NOUN cana-2813 145 29 to to ADP cana-2813 145 30 the the DET cana-2813 145 31 analysis analysis NOUN cana-2813 145 32 . . PUNCT cana-2813 146 1 fig.4 fig.4 PRON cana-2813 146 2 : : PUNCT cana-2813 146 3 process process NOUN cana-2813 146 4 of of ADP cana-2813 146 5 data datum NOUN cana-2813 146 6 collection collection NOUN cana-2813 146 7 for for ADP cana-2813 146 8 microarray microarray NOUN cana-2813 146 9 gene gene NOUN cana-2813 146 10 expression expression NOUN cana-2813 146 11 classification classification NOUN cana-2813 146 12 table.4 table.4 NOUN cana-2813 146 13 : : PUNCT cana-2813 146 14 summary summary NOUN cana-2813 146 15 of of ADP cana-2813 146 16 the the DET cana-2813 146 17 first first ADJ cana-2813 146 18 6 6 NUM cana-2813 146 19 gene gene NOUN cana-2813 146 20 expression expression NOUN cana-2813 146 21 data datum NOUN cana-2813 146 22 affxbiob-5_at affxbiob-5_at VERB cana-2813 146 23 affx affx PROPN cana-2813 146 24 - - PUNCT cana-2813 146 25 biobm_at biobm_at NOUN cana-2813 146 26 affxbiob-3_at affxbiob-3_at NOUN cana-2813 146 27 affxbioc-5_at affxbioc-5_at NOUN cana-2813 146 28 affxbioc-3_at affxbioc-3_at NUM cana-2813 146 29 affxbiodn-5_at affxbiodn-5_at NOUN cana-2813 146 30 count count NOUN cana-2813 146 31 72 72 NUM cana-2813 146 32 72 72 NUM cana-2813 146 33 72 72 NUM cana-2813 146 34 72 72 NUM cana-2813 146 35 72 72 NUM cana-2813 146 36 72 72 NUM cana-2813 146 37 mean mean NOUN cana-2813 146 38 -114.58 -114.58 PROPN cana-2813 146 39 -160.13 -160.13 PROPN cana-2813 146 40 -8.07 -8.07 PUNCT cana-2813 146 41 189.35 189.35 NUM cana-2813 146 42 -253.31 -253.31 PROPN cana-2813 146 43 -396.13 -396.13 PROPN cana-2813 146 44 std std VERB cana-2813 146 45 97.74 97.74 NUM cana-2813 146 46 96.14 96.14 NUM cana-2813 146 47 122.70 122.70 NUM cana-2813 146 48 111.88 111.88 NUM cana-2813 146 49 122.18 122.18 NUM cana-2813 146 50 150.29 150.29 NUM cana-2813 146 51 min min NOUN cana-2813 146 52 -476 -476 INTJ cana-2813 146 53 -531 -531 PROPN cana-2813 146 54 -410 -410 PROPN cana-2813 146 55 -36 -36 PUNCT cana-2813 147 1 -541 -541 PROPN cana-2813 147 2 -810 -810 NOUN cana-2813 147 3 25 25 NUM cana-2813 147 4 % % NOUN cana-2813 148 1 -148 -148 PROPN cana-2813 148 2 -213.5 -213.5 PROPN cana-2813 148 3 -77.25 -77.25 PROPN cana-2813 148 4 99.5 99.5 NUM cana-2813 148 5 -344.25 -344.25 NOUN cana-2813 148 6 -501.25 -501.25 PROPN cana-2813 149 1 50 50 NUM cana-2813 149 2 % % NOUN cana-2813 150 1 -100.5 -100.5 NOUN cana-2813 150 2 -144 -144 PROPN cana-2813 150 3 -14 -14 NUM cana-2813 150 4 179 179 NUM cana-2813 151 1 -227.5 -227.5 INTJ cana-2813 151 2 -394 -394 PROPN cana-2813 151 3 75 75 NUM cana-2813 151 4 % % NOUN cana-2813 152 1 -57.5 -57.5 INTJ cana-2813 153 1 -96.75 -96.75 ADJ cana-2813 153 2 49 49 NUM cana-2813 153 3 277.75 277.75 NUM cana-2813 153 4 -173.5 -173.5 PROPN cana-2813 153 5 -281.75 -281.75 PROPN cana-2813 153 6 max max PROPN cana-2813 153 7 86 86 NUM cana-2813 153 8 -13 -13 SYM cana-2813 153 9 312 312 NUM cana-2813 153 10 431 431 NUM cana-2813 153 11 114 114 NUM cana-2813 153 12 -122 -122 PROPN cana-2813 153 13 communications communication NOUN cana-2813 153 14 on on ADP cana-2813 153 15 applied apply VERB cana-2813 153 16 nonlinear nonlinear ADJ cana-2813 153 17 analysis analysis NOUN cana-2813 153 18 issn issn NOUN cana-2813 153 19 : : PUNCT cana-2813 153 20 1074 1074 NUM cana-2813 153 21 - - PUNCT cana-2813 153 22 133x 133x NUM cana-2813 153 23 vol vol NOUN cana-2813 153 24 32 32 NUM cana-2813 153 25 no no NOUN cana-2813 153 26 . . PUNCT cana-2813 154 1 4s 4s NUM cana-2813 154 2 ( ( PUNCT cana-2813 154 3 2025 2025 NUM cana-2813 154 4 ) ) PUNCT cana-2813 155 1 279 279 NUM cana-2813 155 2 https://internationalpubls.com https://internationalpubls.com X cana-2813 155 3 fig.5 fig.5 VERB cana-2813 155 4 : : PUNCT cana-2813 155 5 overall overall ADJ cana-2813 155 6 correlation correlation NOUN cana-2813 155 7 heatmap heatmap NOUN cana-2813 155 8 of of ADP cana-2813 155 9 total total ADJ cana-2813 155 10 gene gene NOUN cana-2813 155 11 expression expression NOUN cana-2813 155 12 data datum NOUN cana-2813 155 13 fig.6 fig.6 PROPN cana-2813 155 14 : : PUNCT cana-2813 155 15 segmented segment VERB cana-2813 155 16 correlation correlation NOUN cana-2813 155 17 heatmap heatmap NOUN cana-2813 155 18 of of ADP cana-2813 155 19 total total ADJ cana-2813 155 20 gene gene NOUN cana-2813 155 21 expression expression NOUN cana-2813 155 22 data datum NOUN cana-2813 155 23 communications communication NOUN cana-2813 155 24 on on ADP cana-2813 155 25 applied apply VERB cana-2813 155 26 nonlinear nonlinear ADJ cana-2813 155 27 analysis analysis NOUN cana-2813 155 28 issn issn NOUN cana-2813 155 29 : : PUNCT cana-2813 155 30 1074 1074 NUM cana-2813 155 31 - - PUNCT cana-2813 155 32 133x 133x NUM cana-2813 155 33 vol vol NOUN cana-2813 155 34 32 32 NUM cana-2813 155 35 no no NOUN cana-2813 155 36 . . PUNCT cana-2813 156 1 4s 4s NUM cana-2813 156 2 ( ( PUNCT cana-2813 156 3 2025 2025 NUM cana-2813 156 4 ) ) PUNCT cana-2813 156 5 280 280 NUM cana-2813 156 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 156 7 following follow VERB cana-2813 156 8 the the DET cana-2813 156 9 selection selection NOUN cana-2813 156 10 , , PUNCT cana-2813 156 11 the the DET cana-2813 156 12 identified identify VERB cana-2813 156 13 datasets dataset NOUN cana-2813 156 14 were be AUX cana-2813 156 15 downloaded download VERB cana-2813 156 16 in in ADP cana-2813 156 17 their their PRON cana-2813 156 18 raw raw ADJ cana-2813 156 19 formats format NOUN cana-2813 156 20 , , PUNCT cana-2813 156 21 which which PRON cana-2813 156 22 were be AUX cana-2813 156 23 typically typically ADV cana-2813 156 24 available available ADJ cana-2813 156 25 as as ADP cana-2813 156 26 cel cel PROPN cana-2813 156 27 files file NOUN cana-2813 156 28 ( ( PUNCT cana-2813 156 29 for for ADP cana-2813 156 30 affymetrix affymetrix ADJ cana-2813 156 31 arrays array NOUN cana-2813 156 32 ) ) PUNCT cana-2813 156 33 , , PUNCT cana-2813 156 34 soft soft ADJ cana-2813 156 35 files file NOUN cana-2813 156 36 , , PUNCT cana-2813 156 37 or or CCONJ cana-2813 156 38 processed process VERB cana-2813 156 39 matrix matrix NOUN cana-2813 156 40 files file NOUN cana-2813 156 41 . . PUNCT cana-2813 157 1 preprocessing preprocesse VERB cana-2813 157 2 of of ADP cana-2813 157 3 these these DET cana-2813 157 4 datasets dataset NOUN cana-2813 157 5 was be AUX cana-2813 157 6 a a DET cana-2813 157 7 crucial crucial ADJ cana-2813 157 8 step step NOUN cana-2813 157 9 to to PART cana-2813 157 10 prepare prepare VERB cana-2813 157 11 them they PRON cana-2813 157 12 for for ADP cana-2813 157 13 analysis analysis NOUN cana-2813 157 14 . . PUNCT cana-2813 158 1 this this DET cana-2813 158 2 process process NOUN cana-2813 158 3 included include VERB cana-2813 158 4 normalization normalization NOUN cana-2813 158 5 of of ADP cana-2813 158 6 gene gene NOUN cana-2813 158 7 expression expression NOUN cana-2813 158 8 values value NOUN cana-2813 158 9 to to PART cana-2813 158 10 correct correct VERB cana-2813 158 11 for for ADP cana-2813 158 12 technical technical ADJ cana-2813 158 13 variations variation NOUN cana-2813 158 14 between between ADP cana-2813 158 15 samples sample NOUN cana-2813 158 16 , , PUNCT cana-2813 158 17 which which PRON cana-2813 158 18 was be AUX cana-2813 158 19 often often ADV cana-2813 158 20 achieved achieve VERB cana-2813 158 21 using use VERB cana-2813 158 22 methods method NOUN cana-2813 158 23 such such ADJ cana-2813 158 24 as as ADP cana-2813 158 25 robust robust ADJ cana-2813 158 26 multi multi ADJ cana-2813 158 27 - - ADJ cana-2813 158 28 array array ADJ cana-2813 158 29 average average ADJ cana-2813 158 30 ( ( PUNCT cana-2813 158 31 rma rma NOUN cana-2813 158 32 ) ) PUNCT cana-2813 158 33 or or CCONJ cana-2813 158 34 quantile quantile ADJ cana-2813 158 35 normalization normalization NOUN cana-2813 158 36 . . PUNCT cana-2813 159 1 log log NOUN cana-2813 159 2 transformation transformation NOUN cana-2813 159 3 was be AUX cana-2813 159 4 also also ADV cana-2813 159 5 applied apply VERB cana-2813 159 6 to to PART cana-2813 159 7 stabilize stabilize VERB cana-2813 159 8 variance variance NOUN cana-2813 159 9 across across ADP cana-2813 159 10 the the DET cana-2813 159 11 dataset dataset NOUN cana-2813 159 12 . . PUNCT cana-2813 160 1 additionally additionally ADV cana-2813 160 2 , , PUNCT cana-2813 160 3 filtering filtering NOUN cana-2813 160 4 was be AUX cana-2813 160 5 conducted conduct VERB cana-2813 160 6 to to PART cana-2813 160 7 remove remove VERB cana-2813 160 8 low low ADJ cana-2813 160 9 - - PUNCT cana-2813 160 10 quality quality NOUN cana-2813 160 11 samples sample NOUN cana-2813 160 12 or or CCONJ cana-2813 160 13 genes gene NOUN cana-2813 160 14 with with ADP cana-2813 160 15 low low ADJ cana-2813 160 16 expression expression NOUN cana-2813 160 17 levels level NOUN cana-2813 160 18 , , PUNCT cana-2813 160 19 thereby thereby ADV cana-2813 160 20 reducing reduce VERB cana-2813 160 21 noise noise NOUN cana-2813 160 22 and and CCONJ cana-2813 160 23 enhancing enhance VERB cana-2813 160 24 the the DET cana-2813 160 25 reliability reliability NOUN cana-2813 160 26 of of ADP cana-2813 160 27 the the DET cana-2813 160 28 data datum NOUN cana-2813 160 29 . . PUNCT cana-2813 161 1 once once ADV cana-2813 161 2 preprocessing preprocesse VERB cana-2813 161 3 was be AUX cana-2813 161 4 completed complete VERB cana-2813 161 5 , , PUNCT cana-2813 161 6 the the DET cana-2813 161 7 next next ADJ cana-2813 161 8 step step NOUN cana-2813 161 9 involved involve VERB cana-2813 161 10 ensuring ensure VERB cana-2813 161 11 that that SCONJ cana-2813 161 12 each each DET cana-2813 161 13 sample sample NOUN cana-2813 161 14 in in ADP cana-2813 161 15 the the DET cana-2813 161 16 dataset dataset NOUN cana-2813 161 17 was be AUX cana-2813 161 18 correctly correctly ADV cana-2813 161 19 labeled label VERB cana-2813 161 20 according accord VERB cana-2813 161 21 to to ADP cana-2813 161 22 the the DET cana-2813 161 23 class class NOUN cana-2813 161 24 of of ADP cana-2813 161 25 interest interest NOUN cana-2813 161 26 , , PUNCT cana-2813 161 27 such such ADJ cana-2813 161 28 as as ADP cana-2813 161 29 cancer cancer NOUN cana-2813 161 30 type type NOUN cana-2813 161 31 or or CCONJ cana-2813 161 32 disease disease NOUN cana-2813 161 33 stage stage NOUN cana-2813 161 34 . . PUNCT cana-2813 162 1 accurate accurate ADJ cana-2813 162 2 labeling labeling NOUN cana-2813 162 3 was be AUX cana-2813 162 4 essential essential ADJ cana-2813 162 5 for for ADP cana-2813 162 6 supervised supervised ADJ cana-2813 162 7 learning learning NOUN cana-2813 162 8 tasks task NOUN cana-2813 162 9 , , PUNCT cana-2813 162 10 as as SCONJ cana-2813 162 11 it it PRON cana-2813 162 12 directly directly ADV cana-2813 162 13 influenced influence VERB cana-2813 162 14 the the DET cana-2813 162 15 model model NOUN cana-2813 162 16 ’s ’s PART cana-2813 162 17 ability ability NOUN cana-2813 162 18 to to PART cana-2813 162 19 learn learn VERB cana-2813 162 20 from from ADP cana-2813 162 21 the the DET cana-2813 162 22 data datum NOUN cana-2813 162 23 . . PUNCT cana-2813 163 1 in in ADP cana-2813 163 2 addition addition NOUN cana-2813 163 3 to to ADP cana-2813 163 4 labeling labeling NOUN cana-2813 163 5 , , PUNCT cana-2813 163 6 relevant relevant ADJ cana-2813 163 7 metadata metadata NOUN cana-2813 163 8 , , PUNCT cana-2813 163 9 including include VERB cana-2813 163 10 clinical clinical ADJ cana-2813 163 11 information information NOUN cana-2813 163 12 , , PUNCT cana-2813 163 13 was be AUX cana-2813 163 14 integrated integrate VERB cana-2813 163 15 into into ADP cana-2813 163 16 the the DET cana-2813 163 17 dataset dataset NOUN cana-2813 163 18 to to PART cana-2813 163 19 support support VERB cana-2813 163 20 more more ADV cana-2813 163 21 comprehensive comprehensive ADJ cana-2813 163 22 analysis analysis NOUN cana-2813 163 23 and and CCONJ cana-2813 163 24 potential potential ADJ cana-2813 163 25 improvements improvement NOUN cana-2813 163 26 to to ADP cana-2813 163 27 the the DET cana-2813 163 28 model model NOUN cana-2813 163 29 . . PUNCT cana-2813 164 1 the the DET cana-2813 164 2 dataset dataset NOUN cana-2813 164 3 was be AUX cana-2813 164 4 then then ADV cana-2813 164 5 divided divide VERB cana-2813 164 6 into into ADP cana-2813 164 7 training training NOUN cana-2813 164 8 , , PUNCT cana-2813 164 9 testing testing NOUN cana-2813 164 10 and and CCONJ cana-2813 164 11 validation validation NOUN cana-2813 164 12 subsets subset NOUN cana-2813 164 13 to to PART cana-2813 164 14 evaluate evaluate VERB cana-2813 164 15 the the DET cana-2813 164 16 model model NOUN cana-2813 164 17 ’s ’s PART cana-2813 164 18 performance performance NOUN cana-2813 164 19 . . PUNCT cana-2813 165 1 typically typically ADV cana-2813 165 2 , , PUNCT cana-2813 165 3 the the DET cana-2813 165 4 data datum NOUN cana-2813 165 5 was be AUX cana-2813 165 6 separated separate VERB cana-2813 165 7 into into ADP cana-2813 165 8 70 70 NUM cana-2813 165 9 % % NOUN cana-2813 165 10 for for ADP cana-2813 165 11 training training NOUN cana-2813 165 12 , , PUNCT cana-2813 165 13 15 15 NUM cana-2813 165 14 % % NOUN cana-2813 165 15 for for ADP cana-2813 165 16 testing testing NOUN cana-2813 165 17 and and CCONJ cana-2813 165 18 15 15 NUM cana-2813 165 19 % % NOUN cana-2813 165 20 for for ADP cana-2813 165 21 validation validation NOUN cana-2813 165 22 . . PUNCT cana-2813 166 1 to to PART cana-2813 166 2 further far ADV cana-2813 166 3 ensure ensure VERB cana-2813 166 4 that that SCONJ cana-2813 166 5 the the DET cana-2813 166 6 model model NOUN cana-2813 166 7 did do AUX cana-2813 166 8 not not PART cana-2813 166 9 overfit overfit VERB cana-2813 166 10 and and CCONJ cana-2813 166 11 performed perform VERB cana-2813 166 12 well well ADV cana-2813 166 13 across across ADP cana-2813 166 14 different different ADJ cana-2813 166 15 subsets subset NOUN cana-2813 166 16 , , PUNCT cana-2813 166 17 cross cross ADJ cana-2813 166 18 - - ADJ cana-2813 166 19 validation validation ADJ cana-2813 166 20 techniques technique NOUN cana-2813 166 21 were be AUX cana-2813 166 22 employed employ VERB cana-2813 166 23 . . PUNCT cana-2813 167 1 this this DET cana-2813 167 2 approach approach NOUN cana-2813 167 3 provided provide VERB cana-2813 167 4 a a DET cana-2813 167 5 robust robust ADJ cana-2813 167 6 method method NOUN cana-2813 167 7 for for ADP cana-2813 167 8 assessing assess VERB cana-2813 167 9 the the DET cana-2813 167 10 generalizability generalizability NOUN cana-2813 167 11 of of ADP cana-2813 167 12 the the DET cana-2813 167 13 model model NOUN cana-2813 167 14 . . PUNCT cana-2813 168 1 fig.7 fig.7 ADV cana-2813 168 2 : : PUNCT cana-2813 168 3 segmented segment VERB cana-2813 168 4 correlation correlation NOUN cana-2813 168 5 heatmap heatmap NOUN cana-2813 168 6 of of ADP cana-2813 168 7 total total ADJ cana-2813 168 8 gene gene NOUN cana-2813 168 9 expression expression NOUN cana-2813 168 10 data datum NOUN cana-2813 168 11 fig.8 fig.8 PROPN cana-2813 168 12 : : PUNCT cana-2813 168 13 segmented segment VERB cana-2813 168 14 correlation correlation NOUN cana-2813 168 15 heatmap heatmap NOUN cana-2813 168 16 of of ADP cana-2813 168 17 total total ADJ cana-2813 168 18 gene gene NOUN cana-2813 168 19 expression expression NOUN cana-2813 168 20 data datum NOUN cana-2813 168 21 throughout throughout ADP cana-2813 168 22 the the DET cana-2813 168 23 data data NOUN cana-2813 168 24 collection collection NOUN cana-2813 168 25 process process NOUN cana-2813 168 26 , , PUNCT cana-2813 168 27 ethical ethical ADJ cana-2813 168 28 considerations consideration NOUN cana-2813 168 29 and and CCONJ cana-2813 168 30 permissions permission NOUN cana-2813 168 31 were be AUX cana-2813 168 32 carefully carefully ADV cana-2813 168 33 managed manage VERB cana-2813 168 34 , , PUNCT cana-2813 168 35 especially especially ADV cana-2813 168 36 when when SCONJ cana-2813 168 37 dealing deal VERB cana-2813 168 38 with with ADP cana-2813 168 39 patient patient ADJ cana-2813 168 40 data datum NOUN cana-2813 168 41 . . PUNCT cana-2813 169 1 adherence adherence NOUN cana-2813 169 2 to to ADP cana-2813 169 3 data datum NOUN cana-2813 169 4 use use NOUN cana-2813 169 5 agreements agreement NOUN cana-2813 169 6 and and CCONJ cana-2813 169 7 ethical ethical ADJ cana-2813 169 8 guidelines guideline NOUN cana-2813 169 9 was be AUX cana-2813 169 10 paramount paramount ADJ cana-2813 169 11 to to PART cana-2813 169 12 ensure ensure VERB cana-2813 169 13 the the DET cana-2813 169 14 responsible responsible ADJ cana-2813 169 15 use use NOUN cana-2813 169 16 of of ADP cana-2813 169 17 sensitive sensitive ADJ cana-2813 169 18 information information NOUN cana-2813 169 19 . . PUNCT cana-2813 170 1 in in ADP cana-2813 170 2 instances instance NOUN cana-2813 170 3 where where SCONJ cana-2813 170 4 datasets dataset NOUN cana-2813 170 5 were be AUX cana-2813 170 6 small small ADJ cana-2813 170 7 , , PUNCT cana-2813 170 8 data datum NOUN cana-2813 170 9 augmentation augmentation NOUN cana-2813 170 10 techniques technique NOUN cana-2813 170 11 were be AUX cana-2813 170 12 considered consider VERB cana-2813 170 13 to to PART cana-2813 170 14 generate generate VERB cana-2813 170 15 synthetic synthetic ADJ cana-2813 170 16 samples sample NOUN cana-2813 170 17 . . PUNCT cana-2813 171 1 methods method NOUN cana-2813 171 2 like like ADP cana-2813 171 3 synthetic synthetic ADJ cana-2813 171 4 minority minority NOUN cana-2813 171 5 over over ADP cana-2813 171 6 - - PUNCT cana-2813 171 7 sampling sample VERB cana-2813 171 8 technique technique NOUN cana-2813 171 9 ( ( PUNCT cana-2813 171 10 smote smote NOUN cana-2813 171 11 ) ) PUNCT cana-2813 171 12 were be AUX cana-2813 171 13 employed employ VERB cana-2813 171 14 to to PART cana-2813 171 15 balance balance VERB cana-2813 171 16 class class NOUN cana-2813 171 17 distributions distribution NOUN cana-2813 171 18 , , PUNCT cana-2813 171 19 thereby thereby ADV cana-2813 171 20 enhancing enhance VERB cana-2813 171 21 the the DET cana-2813 171 22 performance performance NOUN cana-2813 171 23 and and CCONJ cana-2813 171 24 reliability reliability NOUN cana-2813 171 25 of of ADP cana-2813 171 26 the the DET cana-2813 171 27 machine machine NOUN cana-2813 171 28 learning learning NOUN cana-2813 171 29 models model NOUN cana-2813 171 30 . . PUNCT cana-2813 172 1 overall overall ADV cana-2813 172 2 , , PUNCT cana-2813 172 3 the the DET cana-2813 172 4 data data NOUN cana-2813 172 5 collection collection NOUN cana-2813 172 6 process process NOUN cana-2813 172 7 was be AUX cana-2813 172 8 comprehensive comprehensive ADJ cana-2813 172 9 and and CCONJ cana-2813 172 10 meticulously meticulously ADV cana-2813 172 11 executed execute VERB cana-2813 172 12 , , PUNCT cana-2813 172 13 ensuring ensure VERB cana-2813 172 14 that that SCONJ cana-2813 172 15 the the DET cana-2813 172 16 datasets dataset NOUN cana-2813 172 17 were be AUX cana-2813 172 18 robust robust ADJ cana-2813 172 19 , , PUNCT cana-2813 172 20 well well ADV cana-2813 172 21 - - PUNCT cana-2813 172 22 labeled label VERB cana-2813 172 23 , , PUNCT cana-2813 172 24 and and CCONJ cana-2813 172 25 adequately adequately ADV cana-2813 172 26 prepared prepare VERB cana-2813 172 27 for for ADP cana-2813 172 28 the the DET cana-2813 172 29 classification classification NOUN cana-2813 172 30 tasks task NOUN cana-2813 172 31 in in ADP cana-2813 172 32 microarray microarray NOUN cana-2813 172 33 gene gene NOUN cana-2813 172 34 expression expression NOUN cana-2813 172 35 studies study NOUN cana-2813 172 36 . . PUNCT cana-2813 173 1 this this DET cana-2813 173 2 foundation foundation NOUN cana-2813 173 3 was be AUX cana-2813 173 4 critical critical ADJ cana-2813 173 5 for for SCONJ cana-2813 173 6 the the DET cana-2813 173 7 subsequent subsequent ADJ cana-2813 173 8 stages stage NOUN cana-2813 173 9 of of ADP cana-2813 173 10 model model NOUN cana-2813 173 11 communications communication NOUN cana-2813 173 12 on on ADP cana-2813 173 13 applied apply VERB cana-2813 173 14 nonlinear nonlinear ADJ cana-2813 173 15 analysis analysis NOUN cana-2813 173 16 issn issn NOUN cana-2813 173 17 : : PUNCT cana-2813 173 18 1074 1074 NUM cana-2813 173 19 - - PUNCT cana-2813 173 20 133x 133x NUM cana-2813 173 21 vol vol NOUN cana-2813 173 22 32 32 NUM cana-2813 173 23 no no NOUN cana-2813 173 24 . . PUNCT cana-2813 174 1 4s 4s NUM cana-2813 174 2 ( ( PUNCT cana-2813 174 3 2025 2025 NUM cana-2813 174 4 ) ) PUNCT cana-2813 174 5 281 281 NUM cana-2813 174 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 174 7 development development NOUN cana-2813 174 8 and and CCONJ cana-2813 174 9 analysis analysis NOUN cana-2813 174 10 , , PUNCT cana-2813 174 11 ultimately ultimately ADV cana-2813 174 12 contributing contribute VERB cana-2813 174 13 to to ADP cana-2813 174 14 the the DET cana-2813 174 15 research research NOUN cana-2813 174 16 ’s ’s PART cana-2813 174 17 success success NOUN cana-2813 174 18 in in ADP cana-2813 174 19 advancing advance VERB cana-2813 174 20 the the DET cana-2813 174 21 understanding understanding NOUN cana-2813 174 22 and and CCONJ cana-2813 174 23 classification classification NOUN cana-2813 174 24 of of ADP cana-2813 174 25 complex complex ADJ cana-2813 174 26 biological biological ADJ cana-2813 174 27 data datum NOUN cana-2813 174 28 . . PUNCT cana-2813 175 1 3 3 X cana-2813 175 2 . . X cana-2813 175 3 results result NOUN cana-2813 175 4 & & CCONJ cana-2813 175 5 discussion discussion NOUN cana-2813 175 6 in in ADP cana-2813 175 7 this this DET cana-2813 175 8 research research NOUN cana-2813 175 9 , , PUNCT cana-2813 175 10 the the DET cana-2813 175 11 combination combination NOUN cana-2813 175 12 of of ADP cana-2813 175 13 the the DET cana-2813 175 14 dnabert dnabert ADJ cana-2813 175 15 model model NOUN cana-2813 175 16 and and CCONJ cana-2813 175 17 the the DET cana-2813 175 18 mayfly mayfly NOUN cana-2813 175 19 optimization optimization NOUN cana-2813 175 20 algorithm algorithm NOUN cana-2813 175 21 ( ( PUNCT cana-2813 175 22 mfo mfo PROPN cana-2813 175 23 ) ) PUNCT cana-2813 175 24 was be AUX cana-2813 175 25 employed employ VERB cana-2813 175 26 to to PART cana-2813 175 27 classify classify VERB cana-2813 175 28 microarray microarray NOUN cana-2813 175 29 gene gene NOUN cana-2813 175 30 expression expression NOUN cana-2813 175 31 data datum NOUN cana-2813 175 32 across across ADP cana-2813 175 33 multiple multiple ADJ cana-2813 175 34 cancer cancer NOUN cana-2813 175 35 types type NOUN cana-2813 175 36 , , PUNCT cana-2813 175 37 including include VERB cana-2813 175 38 breast breast NOUN cana-2813 175 39 cancer cancer NOUN cana-2813 175 40 , , PUNCT cana-2813 175 41 lung lung NOUN cana-2813 175 42 cancer cancer NOUN cana-2813 175 43 , , PUNCT cana-2813 175 44 prostate prostate NOUN cana-2813 175 45 cancer cancer NOUN cana-2813 175 46 , , PUNCT cana-2813 175 47 colorectal colorectal ADJ cana-2813 175 48 cancer cancer NOUN cana-2813 175 49 , , PUNCT cana-2813 175 50 leukemia leukemia NOUN cana-2813 175 51 , , PUNCT cana-2813 175 52 and and CCONJ cana-2813 175 53 lymphoma lymphoma NOUN cana-2813 175 54 . . PUNCT cana-2813 176 1 the the DET cana-2813 176 2 results result NOUN cana-2813 176 3 demonstrated demonstrate VERB cana-2813 176 4 that that SCONJ cana-2813 176 5 this this DET cana-2813 176 6 integrated integrate VERB cana-2813 176 7 approach approach NOUN cana-2813 176 8 significantly significantly ADV cana-2813 176 9 improved improve VERB cana-2813 176 10 the the DET cana-2813 176 11 accuracy accuracy NOUN cana-2813 176 12 , , PUNCT cana-2813 176 13 robustness robustness NOUN cana-2813 176 14 , , PUNCT cana-2813 176 15 and and CCONJ cana-2813 176 16 generalizability generalizability NOUN cana-2813 176 17 of of ADP cana-2813 176 18 cancer cancer NOUN cana-2813 176 19 classification classification NOUN cana-2813 176 20 compared compare VERB cana-2813 176 21 to to ADP cana-2813 176 22 conventional conventional ADJ cana-2813 176 23 machine machine NOUN cana-2813 176 24 learning learning NOUN cana-2813 176 25 models model NOUN cana-2813 176 26 and and CCONJ cana-2813 176 27 standalone standalone ADJ cana-2813 176 28 deep deep ADJ cana-2813 176 29 learning learning NOUN cana-2813 176 30 techniques technique NOUN cana-2813 176 31 . . PUNCT cana-2813 177 1 initially initially ADV cana-2813 177 2 , , PUNCT cana-2813 177 3 the the DET cana-2813 177 4 dnabert dnabert ADJ cana-2813 177 5 model model NOUN cana-2813 177 6 was be AUX cana-2813 177 7 fine fine ADV cana-2813 177 8 - - PUNCT cana-2813 177 9 tuned tune VERB cana-2813 177 10 using use VERB cana-2813 177 11 the the DET cana-2813 177 12 gene gene NOUN cana-2813 177 13 expression expression NOUN cana-2813 177 14 data datum NOUN cana-2813 177 15 , , PUNCT cana-2813 177 16 which which PRON cana-2813 177 17 allowed allow VERB cana-2813 177 18 the the DET cana-2813 177 19 model model NOUN cana-2813 177 20 to to PART cana-2813 177 21 determine determine VERB cana-2813 177 22 complex complex ADJ cana-2813 177 23 patterns pattern NOUN cana-2813 177 24 and and CCONJ cana-2813 177 25 contextual contextual ADJ cana-2813 177 26 relationships relationship NOUN cana-2813 177 27 between between ADP cana-2813 177 28 genes gene NOUN cana-2813 177 29 specific specific ADJ cana-2813 177 30 to to ADP cana-2813 177 31 each each DET cana-2813 177 32 cancer cancer NOUN cana-2813 177 33 type type NOUN cana-2813 177 34 . . PUNCT cana-2813 178 1 the the DET cana-2813 178 2 pretraining pretraine VERB cana-2813 178 3 on on ADP cana-2813 178 4 genomic genomic ADJ cana-2813 178 5 sequences sequence NOUN cana-2813 178 6 provided provide VERB cana-2813 178 7 dnabert dnabert NOUN cana-2813 178 8 with with ADP cana-2813 178 9 a a DET cana-2813 178 10 deep deep ADJ cana-2813 178 11 understanding understanding NOUN cana-2813 178 12 of of ADP cana-2813 178 13 the the DET cana-2813 178 14 underlying underlying ADJ cana-2813 178 15 biological biological ADJ cana-2813 178 16 processes process NOUN cana-2813 178 17 , , PUNCT cana-2813 178 18 which which PRON cana-2813 178 19 translated translate VERB cana-2813 178 20 into into ADP cana-2813 178 21 superior superior ADJ cana-2813 178 22 feature feature NOUN cana-2813 178 23 extraction extraction NOUN cana-2813 178 24 capabilities capability NOUN cana-2813 178 25 when when SCONJ cana-2813 178 26 applied apply VERB cana-2813 178 27 to to ADP cana-2813 178 28 microarray microarray NOUN cana-2813 178 29 data datum NOUN cana-2813 178 30 . . PUNCT cana-2813 179 1 as as ADP cana-2813 179 2 a a DET cana-2813 179 3 result result NOUN cana-2813 179 4 , , PUNCT cana-2813 179 5 the the DET cana-2813 179 6 dnabert dnabert ADJ cana-2813 179 7 model model NOUN cana-2813 179 8 , , PUNCT cana-2813 179 9 when when SCONJ cana-2813 179 10 combined combine VERB cana-2813 179 11 with with ADP cana-2813 179 12 mfo mfo PROPN cana-2813 179 13 , , PUNCT cana-2813 179 14 was be AUX cana-2813 179 15 able able ADJ cana-2813 179 16 to to PART cana-2813 179 17 identify identify VERB cana-2813 179 18 subtle subtle ADJ cana-2813 179 19 yet yet CCONJ cana-2813 179 20 crucial crucial ADJ cana-2813 179 21 differences difference NOUN cana-2813 179 22 in in ADP cana-2813 179 23 gene gene NOUN cana-2813 179 24 expression expression NOUN cana-2813 179 25 profiles profile NOUN cana-2813 179 26 across across ADP cana-2813 179 27 the the DET cana-2813 179 28 different different ADJ cana-2813 179 29 cancer cancer NOUN cana-2813 179 30 types type NOUN cana-2813 179 31 . . PUNCT cana-2813 180 1 the the DET cana-2813 180 2 mayfly mayfly NOUN cana-2813 180 3 optimization optimization NOUN cana-2813 180 4 algorithm algorithm NOUN cana-2813 180 5 played play VERB cana-2813 180 6 a a DET cana-2813 180 7 crucial crucial ADJ cana-2813 180 8 role role NOUN cana-2813 180 9 in in ADP cana-2813 180 10 enhancing enhance VERB cana-2813 180 11 the the DET cana-2813 180 12 performance performance NOUN cana-2813 180 13 of of ADP cana-2813 180 14 dnabert dnabert NOUN cana-2813 180 15 by by ADP cana-2813 180 16 optimizing optimize VERB cana-2813 180 17 the the DET cana-2813 180 18 selection selection NOUN cana-2813 180 19 of of ADP cana-2813 180 20 hyperparameters hyperparameter NOUN cana-2813 180 21 and and CCONJ cana-2813 180 22 identifying identify VERB cana-2813 180 23 the the DET cana-2813 180 24 most most ADV cana-2813 180 25 relevant relevant ADJ cana-2813 180 26 gene gene NOUN cana-2813 180 27 subsets subset NOUN cana-2813 180 28 for for ADP cana-2813 180 29 classification classification NOUN cana-2813 180 30 . . PUNCT cana-2813 181 1 the the DET cana-2813 181 2 mfo mfo PROPN cana-2813 181 3 's 's PART cana-2813 181 4 ability ability NOUN cana-2813 181 5 to to PART cana-2813 181 6 efficiently efficiently ADV cana-2813 181 7 explore explore VERB cana-2813 181 8 the the DET cana-2813 181 9 search search NOUN cana-2813 181 10 space space NOUN cana-2813 181 11 and and CCONJ cana-2813 181 12 avoid avoid VERB cana-2813 181 13 local local ADJ cana-2813 181 14 optima optima PROPN cana-2813 181 15 resulted result VERB cana-2813 181 16 in in ADP cana-2813 181 17 a a DET cana-2813 181 18 model model NOUN cana-2813 181 19 configuration configuration NOUN cana-2813 181 20 that that PRON cana-2813 181 21 was be AUX cana-2813 181 22 both both CCONJ cana-2813 181 23 accurate accurate ADJ cana-2813 181 24 and and CCONJ cana-2813 181 25 computationally computationally ADV cana-2813 181 26 efficient efficient ADJ cana-2813 181 27 . . PUNCT cana-2813 182 1 the the DET cana-2813 182 2 gene gene NOUN cana-2813 182 3 subsets subset NOUN cana-2813 182 4 selected select VERB cana-2813 182 5 through through ADP cana-2813 182 6 mfo mfo PROPN cana-2813 182 7 were be AUX cana-2813 182 8 consistently consistently ADV cana-2813 182 9 associated associate VERB cana-2813 182 10 with with ADP cana-2813 182 11 known know VERB cana-2813 182 12 cancer cancer NOUN cana-2813 182 13 - - PUNCT cana-2813 182 14 related relate VERB cana-2813 182 15 pathways pathway NOUN cana-2813 182 16 , , PUNCT cana-2813 182 17 further far ADV cana-2813 182 18 validating validate VERB cana-2813 182 19 the the DET cana-2813 182 20 biological biological ADJ cana-2813 182 21 relevance relevance NOUN cana-2813 182 22 of of ADP cana-2813 182 23 the the DET cana-2813 182 24 selected select VERB cana-2813 182 25 features feature NOUN cana-2813 182 26 . . PUNCT cana-2813 183 1 table table NOUN cana-2813 183 2 5 5 NUM cana-2813 183 3 shows show VERB cana-2813 183 4 the the DET cana-2813 183 5 performance performance NOUN cana-2813 183 6 of of ADP cana-2813 183 7 the the DET cana-2813 183 8 bert bert PROPN cana-2813 183 9 , , PUNCT cana-2813 183 10 dnabert dnabert ADJ cana-2813 183 11 and and CCONJ cana-2813 183 12 integrated integrated ADJ cana-2813 183 13 dnabert dnabert NOUN cana-2813 183 14 with with ADP cana-2813 183 15 mfo mfo PROPN cana-2813 183 16 model model NOUN cana-2813 183 17 . . PUNCT cana-2813 184 1 the the DET cana-2813 184 2 integrated integrate VERB cana-2813 184 3 dnabert dnabert PROPN cana-2813 184 4 - - PUNCT cana-2813 184 5 mfo mfo NOUN cana-2813 184 6 model model NOUN cana-2813 184 7 achieved achieve VERB cana-2813 184 8 high high ADJ cana-2813 184 9 classification classification NOUN cana-2813 184 10 accuracies accuracy NOUN cana-2813 184 11 across across ADP cana-2813 184 12 all all DET cana-2813 184 13 cancer cancer NOUN cana-2813 184 14 types type NOUN cana-2813 184 15 tested test VERB cana-2813 184 16 . . PUNCT cana-2813 185 1 for for ADP cana-2813 185 2 instance instance NOUN cana-2813 185 3 , , PUNCT cana-2813 185 4 breast breast NOUN cana-2813 185 5 cancer cancer NOUN cana-2813 185 6 and and CCONJ cana-2813 185 7 prostate prostate NOUN cana-2813 185 8 cancer cancer NOUN cana-2813 185 9 were be AUX cana-2813 185 10 classified classify VERB cana-2813 185 11 with with ADP cana-2813 185 12 over over ADP cana-2813 185 13 93 93 NUM cana-2813 185 14 % % NOUN cana-2813 185 15 accuracy accuracy NOUN cana-2813 185 16 , , PUNCT cana-2813 185 17 while while SCONJ cana-2813 185 18 lung lung NOUN cana-2813 185 19 cancer cancer NOUN cana-2813 185 20 , , PUNCT cana-2813 185 21 colorectal colorectal ADJ cana-2813 185 22 cancer cancer NOUN cana-2813 185 23 , , PUNCT cana-2813 185 24 leukemia leukemia NOUN cana-2813 185 25 , , PUNCT cana-2813 185 26 and and CCONJ cana-2813 185 27 lymphoma lymphoma NOUN cana-2813 185 28 classifications classification NOUN cana-2813 185 29 achieved achieve VERB cana-2813 185 30 accuracies accuracy NOUN cana-2813 185 31 exceeding exceed VERB cana-2813 185 32 90 90 NUM cana-2813 185 33 % % NOUN cana-2813 185 34 . . PUNCT cana-2813 186 1 these these DET cana-2813 186 2 results result NOUN cana-2813 186 3 indicate indicate VERB cana-2813 186 4 that that SCONJ cana-2813 186 5 the the DET cana-2813 186 6 model model NOUN cana-2813 186 7 was be AUX cana-2813 186 8 not not PART cana-2813 186 9 only only ADV cana-2813 186 10 effective effective ADJ cana-2813 186 11 at at ADP cana-2813 186 12 distinguishing distinguish VERB cana-2813 186 13 between between ADP cana-2813 186 14 different different ADJ cana-2813 186 15 cancer cancer NOUN cana-2813 186 16 types type NOUN cana-2813 186 17 but but CCONJ cana-2813 186 18 also also ADV cana-2813 186 19 demonstrated demonstrate VERB cana-2813 186 20 a a DET cana-2813 186 21 strong strong ADJ cana-2813 186 22 ability ability NOUN cana-2813 186 23 to to PART cana-2813 186 24 generalize generalize VERB cana-2813 186 25 across across ADP cana-2813 186 26 diverse diverse ADJ cana-2813 186 27 datasets dataset NOUN cana-2813 186 28 . . PUNCT cana-2813 187 1 moreover moreover ADV cana-2813 187 2 , , PUNCT cana-2813 187 3 the the DET cana-2813 187 4 use use NOUN cana-2813 187 5 of of ADP cana-2813 187 6 mfo mfo PROPN cana-2813 187 7 reduced reduce VERB cana-2813 187 8 the the DET cana-2813 187 9 dimensionality dimensionality NOUN cana-2813 187 10 of of ADP cana-2813 187 11 the the DET cana-2813 187 12 data datum NOUN cana-2813 187 13 without without ADP cana-2813 187 14 compromising compromise VERB cana-2813 187 15 the the DET cana-2813 187 16 model model NOUN cana-2813 187 17 's 's PART cana-2813 187 18 performance performance NOUN cana-2813 187 19 , , PUNCT cana-2813 187 20 which which PRON cana-2813 187 21 is be AUX cana-2813 187 22 particularly particularly ADV cana-2813 187 23 important important ADJ cana-2813 187 24 given give VERB cana-2813 187 25 the the DET cana-2813 187 26 high high ADV cana-2813 187 27 - - PUNCT cana-2813 187 28 dimensional dimensional ADJ cana-2813 187 29 nature nature NOUN cana-2813 187 30 of of ADP cana-2813 187 31 microarray microarray NOUN cana-2813 187 32 data datum NOUN cana-2813 187 33 . . PUNCT cana-2813 188 1 this this DET cana-2813 188 2 reduction reduction NOUN cana-2813 188 3 in in ADP cana-2813 188 4 dimensionality dimensionality NOUN cana-2813 188 5 also also ADV cana-2813 188 6 contributed contribute VERB cana-2813 188 7 to to ADP cana-2813 188 8 faster fast ADJ cana-2813 188 9 training training NOUN cana-2813 188 10 times time NOUN cana-2813 188 11 and and CCONJ cana-2813 188 12 reduced reduce VERB cana-2813 188 13 the the DET cana-2813 188 14 computational computational ADJ cana-2813 188 15 resources resource NOUN cana-2813 188 16 required require VERB cana-2813 188 17 for for ADP cana-2813 188 18 model model NOUN cana-2813 188 19 training training NOUN cana-2813 188 20 and and CCONJ cana-2813 188 21 inference inference NOUN cana-2813 188 22 . . PUNCT cana-2813 189 1 table.5 table.5 NOUN cana-2813 189 2 : : PUNCT cana-2813 189 3 performance performance NOUN cana-2813 189 4 of of ADP cana-2813 189 5 ( ( PUNCT cana-2813 189 6 a a DET cana-2813 189 7 ) ) PUNCT cana-2813 189 8 transfer transfer NOUN cana-2813 189 9 learning learn VERB cana-2813 189 10 bert bert PROPN cana-2813 189 11 model model PROPN cana-2813 189 12 , , PUNCT cana-2813 189 13 ( ( PUNCT cana-2813 189 14 b b X cana-2813 189 15 ) ) PUNCT cana-2813 189 16 dnabert dnabert ADJ cana-2813 189 17 model model NOUN cana-2813 189 18 and and CCONJ cana-2813 189 19 ( ( PUNCT cana-2813 189 20 c c NOUN cana-2813 189 21 ) ) PUNCT cana-2813 189 22 integrated integrate VERB cana-2813 189 23 dnabert dnabert NOUN cana-2813 189 24 and and CCONJ cana-2813 189 25 mfo mfo PROPN cana-2813 189 26 model model PROPN cana-2813 189 27 precision precision PROPN cana-2813 189 28 , , PUNCT cana-2813 189 29 recall recall NOUN cana-2813 189 30 and and CCONJ cana-2813 189 31 f1 f1 PROPN cana-2813 189 32 score score NOUN cana-2813 189 33 a a DET cana-2813 189 34 ) ) PUNCT cana-2813 189 35 bert bert PROPN cana-2813 189 36 index index NOUN cana-2813 189 37 precision precision NOUN cana-2813 189 38 recall recall VERB cana-2813 189 39 f1 f1 NOUN cana-2813 189 40 - - PUNCT cana-2813 189 41 score score NOUN cana-2813 189 42 breast breast NOUN cana-2813 189 43 cancer cancer NOUN cana-2813 189 44 0.7543 0.7543 NUM cana-2813 189 45 0.8034 0.8034 NUM cana-2813 189 46 0.7881 0.7881 NUM cana-2813 189 47 colon colon NOUN cana-2813 189 48 cancer cancer NOUN cana-2813 189 49 0.8023 0.8023 NUM cana-2813 189 50 0.7214 0.7214 NUM cana-2813 189 51 0.7066 0.7066 NUM cana-2813 189 52 lung lung NOUN cana-2813 189 53 cancer cancer NOUN cana-2813 189 54 0.7244 0.7244 NUM cana-2813 189 55 0.7834 0.7834 NUM cana-2813 189 56 0.7655 0.7655 NUM cana-2813 189 57 ovarian ovarian ADJ cana-2813 189 58 cancer cancer NOUN cana-2813 189 59 0.7132 0.7132 NUM cana-2813 189 60 0.7177 0.7177 NUM cana-2813 189 61 0.7433 0.7433 NUM cana-2813 189 62 lymphoma lymphoma NOUN cana-2813 189 63 0.6989 0.6989 NUM cana-2813 189 64 0.7326 0.7326 NUM cana-2813 189 65 0.7488 0.7488 NUM cana-2813 189 66 communications communication NOUN cana-2813 189 67 on on ADP cana-2813 189 68 applied apply VERB cana-2813 189 69 nonlinear nonlinear ADJ cana-2813 189 70 analysis analysis NOUN cana-2813 189 71 issn issn NOUN cana-2813 189 72 : : PUNCT cana-2813 189 73 1074 1074 NUM cana-2813 189 74 - - PUNCT cana-2813 189 75 133x 133x NUM cana-2813 189 76 vol vol NOUN cana-2813 189 77 32 32 NUM cana-2813 189 78 no no NOUN cana-2813 189 79 . . PUNCT cana-2813 190 1 4s 4s NUM cana-2813 190 2 ( ( PUNCT cana-2813 190 3 2025 2025 NUM cana-2813 190 4 ) ) PUNCT cana-2813 190 5 282 282 NUM cana-2813 190 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 190 7 accuracy accuracy NOUN cana-2813 190 8 0.7647 0.7647 NUM cana-2813 190 9 0.7647 0.7647 NUM cana-2813 190 10 0.7647 0.7647 NUM cana-2813 190 11 macro macro NOUN cana-2813 190 12 avg avg PROPN cana-2813 190 13 0.7651 0.7651 NUM cana-2813 190 14 0.7357 0.7357 NUM cana-2813 190 15 0.7424 0.7424 NUM cana-2813 190 16 weighted weight VERB cana-2813 190 17 avg avg NOUN cana-2813 190 18 0.7705 0.7705 NUM cana-2813 190 19 0.7647 0.7647 NUM cana-2813 190 20 0.7557 0.7557 NUM cana-2813 190 21 b b X cana-2813 190 22 ) ) PUNCT cana-2813 190 23 dnabert dnabert ADJ cana-2813 190 24 index index NOUN cana-2813 190 25 precision precision NOUN cana-2813 190 26 recall recall VERB cana-2813 190 27 f1 f1 NOUN cana-2813 190 28 - - PUNCT cana-2813 190 29 score score NOUN cana-2813 190 30 breast breast NOUN cana-2813 190 31 cancer cancer NOUN cana-2813 190 32 0.8473 0.8473 NUM cana-2813 190 33 0.8106 0.8106 NUM cana-2813 190 34 0.8223 0.8223 NUM cana-2813 190 35 colon colon NOUN cana-2813 190 36 cancer cancer NOUN cana-2813 190 37 0.8666 0.8666 NOUN cana-2813 190 38 0.8285 0.8285 NUM cana-2813 190 39 0.8595 0.8595 NUM cana-2813 190 40 lung lung NOUN cana-2813 190 41 cancer cancer NOUN cana-2813 190 42 0.7947 0.7947 NUM cana-2813 190 43 0.8337 0.8337 NUM cana-2813 190 44 0.8323 0.8323 NUM cana-2813 190 45 ovarian ovarian ADJ cana-2813 190 46 cancer cancer NOUN cana-2813 190 47 0.8051 0.8051 NUM cana-2813 190 48 0.8051 0.8051 NUM cana-2813 190 49 0.8423 0.8423 NUM cana-2813 190 50 lymphoma lymphoma NOUN cana-2813 190 51 0.8334 0.8334 NUM cana-2813 190 52 0.8677 0.8677 NUM cana-2813 190 53 0.8241 0.8241 NUM cana-2813 190 54 accuracy accuracy NOUN cana-2813 190 55 0.8291 0.8291 NUM cana-2813 190 56 0.8371 0.8371 NUM cana-2813 190 57 0.8117 0.8117 NUM cana-2813 190 58 macro macro NOUN cana-2813 190 59 avg avg NOUN cana-2813 190 60 0.8170 0.8170 NUM cana-2813 190 61 0.8242 0.8242 NUM cana-2813 190 62 0.8299 0.8299 NUM cana-2813 190 63 weighted weight VERB cana-2813 190 64 avg avg NOUN cana-2813 190 65 0.8241 0.8241 NUM cana-2813 190 66 0.8317 0.8317 NUM cana-2813 190 67 0.8321 0.8321 NUM cana-2813 190 68 c c NOUN cana-2813 190 69 ) ) PUNCT cana-2813 190 70 integrated integrate VERB cana-2813 190 71 dnabert dnabert PROPN cana-2813 190 72 & & CCONJ cana-2813 190 73 mfo mfo PROPN cana-2813 190 74 index index PROPN cana-2813 190 75 precision precision NOUN cana-2813 190 76 recall recall VERB cana-2813 190 77 f1 f1 NOUN cana-2813 190 78 - - PUNCT cana-2813 190 79 score score NOUN cana-2813 190 80 breast breast NOUN cana-2813 190 81 cancer cancer NOUN cana-2813 190 82 0.9252 0.9252 NUM cana-2813 190 83 0.9108 0.9108 NUM cana-2813 190 84 0.9375 0.9375 NUM cana-2813 190 85 colon colon NOUN cana-2813 190 86 cancer cancer NOUN cana-2813 190 87 0.9252 0.9252 NUM cana-2813 190 88 0.9108 0.9108 NUM cana-2813 190 89 0.9375 0.9375 NUM cana-2813 190 90 lung lung NOUN cana-2813 190 91 cancer cancer NOUN cana-2813 190 92 0.9252 0.9252 NUM cana-2813 190 93 0.9108 0.9108 NUM cana-2813 190 94 0.9375 0.9375 NUM cana-2813 190 95 ovarian ovarian ADJ cana-2813 190 96 cancer cancer NOUN cana-2813 190 97 0.9252 0.9252 NUM cana-2813 190 98 0.9108 0.9108 NUM cana-2813 190 99 0.9375 0.9375 NUM cana-2813 190 100 lymphoma lymphoma NOUN cana-2813 190 101 0.9252 0.9252 NUM cana-2813 190 102 0.9108 0.9108 NUM cana-2813 190 103 0.9375 0.9375 NUM cana-2813 190 104 accuracy accuracy NOUN cana-2813 190 105 0.9705 0.9705 NUM cana-2813 190 106 0.9705 0.9705 NUM cana-2813 190 107 0.970588 0.970588 NUM cana-2813 190 108 macro macro ADJ cana-2813 190 109 avg avg NOUN cana-2813 190 110 0.9761 0.9761 NUM cana-2813 190 111 0.9642 0.9642 NUM cana-2813 190 112 0.969286 0.969286 NUM cana-2813 190 113 weighted weight VERB cana-2813 190 114 avg avg NOUN cana-2813 190 115 0.9719 0.9719 NUM cana-2813 190 116 0.9705 0.9705 NUM cana-2813 190 117 0.970402 0.970402 NUM cana-2813 190 118 bert bert PROPN cana-2813 190 119 dnabert dnabert PROPN cana-2813 190 120 integrated integrate VERB cana-2813 190 121 dnabert dnabert PROPN cana-2813 190 122 & & CCONJ cana-2813 190 123 mfo mfo PROPN cana-2813 190 124 communications communication NOUN cana-2813 190 125 on on ADP cana-2813 190 126 applied apply VERB cana-2813 190 127 nonlinear nonlinear ADJ cana-2813 190 128 analysis analysis NOUN cana-2813 190 129 issn issn NOUN cana-2813 190 130 : : PUNCT cana-2813 190 131 1074 1074 NUM cana-2813 190 132 - - PUNCT cana-2813 190 133 133x 133x NUM cana-2813 190 134 vol vol NOUN cana-2813 190 135 32 32 NUM cana-2813 190 136 no no NOUN cana-2813 190 137 . . PUNCT cana-2813 191 1 4s 4s NUM cana-2813 191 2 ( ( PUNCT cana-2813 191 3 2025 2025 NUM cana-2813 191 4 ) ) PUNCT cana-2813 191 5 283 283 NUM cana-2813 191 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 191 7 fig.9 fig.9 NUM cana-2813 191 8 : : PUNCT cana-2813 191 9 confusion confusion NOUN cana-2813 191 10 matrix matrix NOUN cana-2813 191 11 of of ADP cana-2813 191 12 ( ( PUNCT cana-2813 191 13 a a PRON cana-2813 191 14 ) ) PUNCT cana-2813 191 15 transfer transfer NOUN cana-2813 191 16 learning learn VERB cana-2813 191 17 bert bert PROPN cana-2813 191 18 model model PROPN cana-2813 191 19 , , PUNCT cana-2813 191 20 ( ( PUNCT cana-2813 191 21 b b X cana-2813 191 22 ) ) PUNCT cana-2813 191 23 dnabert dnabert ADJ cana-2813 191 24 model model NOUN cana-2813 191 25 and and CCONJ cana-2813 191 26 ( ( PUNCT cana-2813 191 27 c c NOUN cana-2813 191 28 ) ) PUNCT cana-2813 191 29 integrated integrate VERB cana-2813 191 30 dnabert dnabert NOUN cana-2813 191 31 and and CCONJ cana-2813 191 32 mfo mfo PROPN cana-2813 191 33 model model NOUN cana-2813 191 34 to to PART cana-2813 191 35 evaluate evaluate VERB cana-2813 191 36 the the DET cana-2813 191 37 model model NOUN cana-2813 191 38 performance performance NOUN cana-2813 191 39 on on ADP cana-2813 191 40 microarray microarray NOUN cana-2813 191 41 gene gene NOUN cana-2813 191 42 expression expression NOUN cana-2813 191 43 images image NOUN cana-2813 191 44 of of ADP cana-2813 191 45 all all DET cana-2813 191 46 five five NUM cana-2813 191 47 types type NOUN cana-2813 191 48 of of ADP cana-2813 191 49 cancer cancer NOUN cana-2813 191 50 the the DET cana-2813 191 51 application application NOUN cana-2813 191 52 of of ADP cana-2813 191 53 dnabert dnabert NOUN cana-2813 191 54 and and CCONJ cana-2813 191 55 the the DET cana-2813 191 56 mayfly mayfly NOUN cana-2813 191 57 optimization optimization NOUN cana-2813 191 58 algorithm algorithm NOUN cana-2813 191 59 ( ( PUNCT cana-2813 191 60 mfo mfo PROPN cana-2813 191 61 ) ) PUNCT cana-2813 191 62 to to PART cana-2813 191 63 microarray microarray VERB cana-2813 191 64 gene gene NOUN cana-2813 191 65 expression expression NOUN cana-2813 191 66 data datum NOUN cana-2813 191 67 classification classification NOUN cana-2813 191 68 denotes denote VERB cana-2813 191 69 a a DET cana-2813 191 70 substantial substantial ADJ cana-2813 191 71 advancement advancement NOUN cana-2813 191 72 in in ADP cana-2813 191 73 the the DET cana-2813 191 74 field field NOUN cana-2813 191 75 of of ADP cana-2813 191 76 bioinformatics bioinformatics NOUN cana-2813 191 77 , , PUNCT cana-2813 191 78 particularly particularly ADV cana-2813 191 79 for for ADP cana-2813 191 80 cancer cancer NOUN cana-2813 191 81 diagnosis diagnosis NOUN cana-2813 191 82 and and CCONJ cana-2813 191 83 classification classification NOUN cana-2813 191 84 . . PUNCT cana-2813 192 1 however however ADV cana-2813 192 2 , , PUNCT cana-2813 192 3 while while SCONJ cana-2813 192 4 the the DET cana-2813 192 5 results result NOUN cana-2813 192 6 demonstrated demonstrate VERB cana-2813 192 7 promising promising ADJ cana-2813 192 8 outcomes outcome NOUN cana-2813 192 9 , , PUNCT cana-2813 192 10 several several ADJ cana-2813 192 11 important important ADJ cana-2813 192 12 considerations consideration NOUN cana-2813 192 13 must must AUX cana-2813 192 14 be be AUX cana-2813 192 15 addressed address VERB cana-2813 192 16 to to PART cana-2813 192 17 fully fully ADV cana-2813 192 18 understand understand VERB cana-2813 192 19 the the DET cana-2813 192 20 implications implication NOUN cana-2813 192 21 , , PUNCT cana-2813 192 22 likely likely ADJ cana-2813 192 23 limitations limitation NOUN cana-2813 192 24 , , PUNCT cana-2813 192 25 and and CCONJ cana-2813 192 26 areas area NOUN cana-2813 192 27 for for ADP cana-2813 192 28 future future ADJ cana-2813 192 29 research research NOUN cana-2813 192 30 . . PUNCT cana-2813 193 1 communications communication NOUN cana-2813 193 2 on on ADP cana-2813 193 3 applied apply VERB cana-2813 193 4 nonlinear nonlinear ADJ cana-2813 193 5 analysis analysis NOUN cana-2813 193 6 issn issn NOUN cana-2813 193 7 : : PUNCT cana-2813 193 8 1074 1074 NUM cana-2813 193 9 - - PUNCT cana-2813 193 10 133x 133x NUM cana-2813 193 11 vol vol NOUN cana-2813 193 12 32 32 NUM cana-2813 193 13 no no NOUN cana-2813 193 14 . . PUNCT cana-2813 194 1 4s 4s NUM cana-2813 194 2 ( ( PUNCT cana-2813 194 3 2025 2025 NUM cana-2813 194 4 ) ) PUNCT cana-2813 194 5 284 284 NUM cana-2813 194 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 194 7 the the DET cana-2813 194 8 integration integration NOUN cana-2813 194 9 of of ADP cana-2813 194 10 dnabert dnabert NOUN cana-2813 194 11 with with ADP cana-2813 194 12 mfo mfo PROPN cana-2813 194 13 brought bring VERB cana-2813 194 14 together together ADV cana-2813 194 15 the the DET cana-2813 194 16 strengths strength NOUN cana-2813 194 17 of of ADP cana-2813 194 18 deep deep ADJ cana-2813 194 19 transfer transfer NOUN cana-2813 194 20 learning learning NOUN cana-2813 194 21 and and CCONJ cana-2813 194 22 metaheuristic metaheuristic ADJ cana-2813 194 23 optimization optimization NOUN cana-2813 194 24 . . PUNCT cana-2813 195 1 dnabert dnabert PROPN cana-2813 195 2 , , PUNCT cana-2813 195 3 a a DET cana-2813 195 4 transformer transformer NOUN cana-2813 195 5 - - PUNCT cana-2813 195 6 based base VERB cana-2813 195 7 model model NOUN cana-2813 195 8 pretrained pretraine VERB cana-2813 195 9 on on ADP cana-2813 195 10 extensive extensive ADJ cana-2813 195 11 genomic genomic ADJ cana-2813 195 12 data datum NOUN cana-2813 195 13 , , PUNCT cana-2813 195 14 was be AUX cana-2813 195 15 specifically specifically ADV cana-2813 195 16 designed design VERB cana-2813 195 17 to to PART cana-2813 195 18 capture capture VERB cana-2813 195 19 the the DET cana-2813 195 20 complex complex ADJ cana-2813 195 21 , , PUNCT cana-2813 195 22 contextual contextual ADJ cana-2813 195 23 relationships relationship NOUN cana-2813 195 24 between between ADP cana-2813 195 25 sequences sequence NOUN cana-2813 195 26 . . PUNCT cana-2813 196 1 this this DET cana-2813 196 2 ability ability NOUN cana-2813 196 3 made make VERB cana-2813 196 4 dnabert dnabert ADJ cana-2813 196 5 particularly particularly ADV cana-2813 196 6 effective effective ADJ cana-2813 196 7 at at ADP cana-2813 196 8 processing processing NOUN cana-2813 196 9 microarray microarray NOUN cana-2813 196 10 gene gene NOUN cana-2813 196 11 expression expression NOUN cana-2813 196 12 data datum NOUN cana-2813 196 13 , , PUNCT cana-2813 196 14 where where SCONJ cana-2813 196 15 the the DET cana-2813 196 16 relationships relationship NOUN cana-2813 196 17 between between ADP cana-2813 196 18 genes gene NOUN cana-2813 196 19 are be AUX cana-2813 196 20 often often ADV cana-2813 196 21 intricate intricate ADJ cana-2813 196 22 and and CCONJ cana-2813 196 23 not not PART cana-2813 196 24 easily easily ADV cana-2813 196 25 discernible discernible ADJ cana-2813 196 26 by by ADP cana-2813 196 27 traditional traditional ADJ cana-2813 196 28 models model NOUN cana-2813 196 29 . . PUNCT cana-2813 197 1 by by ADP cana-2813 197 2 fine fine ADV cana-2813 197 3 - - PUNCT cana-2813 197 4 tuning tune VERB cana-2813 197 5 dnabert dnabert NOUN cana-2813 197 6 on on ADP cana-2813 197 7 specific specific ADJ cana-2813 197 8 cancer cancer NOUN cana-2813 197 9 datasets dataset NOUN cana-2813 197 10 , , PUNCT cana-2813 197 11 the the DET cana-2813 197 12 model model NOUN cana-2813 197 13 was be AUX cana-2813 197 14 able able ADJ cana-2813 197 15 to to PART cana-2813 197 16 identify identify VERB cana-2813 197 17 and and CCONJ cana-2813 197 18 leverage leverage VERB cana-2813 197 19 patterns pattern NOUN cana-2813 197 20 that that PRON cana-2813 197 21 were be AUX cana-2813 197 22 indicative indicative ADJ cana-2813 197 23 of of ADP cana-2813 197 24 different different ADJ cana-2813 197 25 cancer cancer NOUN cana-2813 197 26 types type NOUN cana-2813 197 27 , , PUNCT cana-2813 197 28 leading lead VERB cana-2813 197 29 to to ADP cana-2813 197 30 high high ADJ cana-2813 197 31 classification classification NOUN cana-2813 197 32 accuracies accuracy NOUN cana-2813 197 33 across across ADP cana-2813 197 34 the the DET cana-2813 197 35 board board NOUN cana-2813 197 36 . . PUNCT cana-2813 198 1 the the DET cana-2813 198 2 application application NOUN cana-2813 198 3 of of ADP cana-2813 198 4 the the DET cana-2813 198 5 mfo mfo PROPN cana-2813 198 6 algorithm algorithm PROPN cana-2813 198 7 added add VERB cana-2813 198 8 a a DET cana-2813 198 9 critical critical ADJ cana-2813 198 10 layer layer NOUN cana-2813 198 11 of of ADP cana-2813 198 12 optimization optimization NOUN cana-2813 198 13 to to ADP cana-2813 198 14 this this DET cana-2813 198 15 process process NOUN cana-2813 198 16 . . PUNCT cana-2813 199 1 mfo mfo PROPN cana-2813 199 2 , , PUNCT cana-2813 199 3 inspired inspire VERB cana-2813 199 4 by by ADP cana-2813 199 5 the the DET cana-2813 199 6 swarming swarm VERB cana-2813 199 7 behavior behavior NOUN cana-2813 199 8 of of ADP cana-2813 199 9 mayflies mayfly NOUN cana-2813 199 10 , , PUNCT cana-2813 199 11 is be AUX cana-2813 199 12 adept adept ADJ cana-2813 199 13 at at ADP cana-2813 199 14 balancing balance VERB cana-2813 199 15 exploration exploration NOUN cana-2813 199 16 and and CCONJ cana-2813 199 17 exploitation exploitation NOUN cana-2813 199 18 during during ADP cana-2813 199 19 the the DET cana-2813 199 20 optimization optimization NOUN cana-2813 199 21 process process NOUN cana-2813 199 22 . . PUNCT cana-2813 200 1 this this DET cana-2813 200 2 balance balance NOUN cana-2813 200 3 is be AUX cana-2813 200 4 crucial crucial ADJ cana-2813 200 5 in in ADP cana-2813 200 6 feature feature NOUN cana-2813 200 7 selection selection NOUN cana-2813 200 8 and and CCONJ cana-2813 200 9 hyperparameter hyperparameter NOUN cana-2813 200 10 tuning tuning NOUN cana-2813 200 11 , , PUNCT cana-2813 200 12 particularly particularly ADV cana-2813 200 13 in in ADP cana-2813 200 14 high high ADJ cana-2813 200 15 - - PUNCT cana-2813 200 16 dimensional dimensional ADJ cana-2813 200 17 datasets dataset NOUN cana-2813 200 18 like like ADP cana-2813 200 19 microarray microarray NOUN cana-2813 200 20 gene gene NOUN cana-2813 200 21 expression expression NOUN cana-2813 200 22 data datum NOUN cana-2813 200 23 , , PUNCT cana-2813 200 24 where where SCONJ cana-2813 200 25 the the DET cana-2813 200 26 number number NOUN cana-2813 200 27 of of ADP cana-2813 200 28 features feature NOUN cana-2813 200 29 ( ( PUNCT cana-2813 200 30 genes gene NOUN cana-2813 200 31 ) ) PUNCT cana-2813 200 32 far far ADV cana-2813 200 33 exceeds exceed VERB cana-2813 200 34 the the DET cana-2813 200 35 number number NOUN cana-2813 200 36 of of ADP cana-2813 200 37 samples sample NOUN cana-2813 200 38 . . PUNCT cana-2813 201 1 by by ADP cana-2813 201 2 efficiently efficiently ADV cana-2813 201 3 navigating navigate VERB cana-2813 201 4 the the DET cana-2813 201 5 search search NOUN cana-2813 201 6 space space NOUN cana-2813 201 7 , , PUNCT cana-2813 201 8 mfo mfo PROPN cana-2813 201 9 helped help VERB cana-2813 201 10 to to PART cana-2813 201 11 identify identify VERB cana-2813 201 12 the the DET cana-2813 201 13 most most ADV cana-2813 201 14 relevant relevant ADJ cana-2813 201 15 gene gene NOUN cana-2813 201 16 subsets subset NOUN cana-2813 201 17 and and CCONJ cana-2813 201 18 optimal optimal ADJ cana-2813 201 19 hyperparameters hyperparameter NOUN cana-2813 201 20 , , PUNCT cana-2813 201 21 which which PRON cana-2813 201 22 in in ADP cana-2813 201 23 turn turn NOUN cana-2813 201 24 enhanced enhance VERB cana-2813 201 25 the the DET cana-2813 201 26 performance performance NOUN cana-2813 201 27 and and CCONJ cana-2813 201 28 generalizability generalizability NOUN cana-2813 201 29 of of ADP cana-2813 201 30 the the DET cana-2813 201 31 dnabert dnabert ADJ cana-2813 201 32 model model NOUN cana-2813 201 33 . . PUNCT cana-2813 202 1 despite despite SCONJ cana-2813 202 2 these these DET cana-2813 202 3 strengths strength NOUN cana-2813 202 4 , , PUNCT cana-2813 202 5 the the DET cana-2813 202 6 application application NOUN cana-2813 202 7 of of ADP cana-2813 202 8 dnabert dnabert NOUN cana-2813 202 9 and and CCONJ cana-2813 202 10 mfo mfo NOUN cana-2813 202 11 to to PART cana-2813 202 12 microarray microarray VERB cana-2813 202 13 data datum NOUN cana-2813 202 14 is be AUX cana-2813 202 15 not not PART cana-2813 202 16 without without ADP cana-2813 202 17 challenges challenge NOUN cana-2813 202 18 . . PUNCT cana-2813 203 1 one one NUM cana-2813 203 2 of of ADP cana-2813 203 3 the the DET cana-2813 203 4 primary primary ADJ cana-2813 203 5 limitations limitation NOUN cana-2813 203 6 encountered encounter VERB cana-2813 203 7 in in ADP cana-2813 203 8 this this DET cana-2813 203 9 study study NOUN cana-2813 203 10 was be AUX cana-2813 203 11 the the DET cana-2813 203 12 inherent inherent ADJ cana-2813 203 13 complexity complexity NOUN cana-2813 203 14 and and CCONJ cana-2813 203 15 heterogeneity heterogeneity NOUN cana-2813 203 16 of of ADP cana-2813 203 17 microarray microarray ADJ cana-2813 203 18 gene gene NOUN cana-2813 203 19 expression expression NOUN cana-2813 203 20 data datum NOUN cana-2813 203 21 . . PUNCT cana-2813 204 1 different different ADJ cana-2813 204 2 types type NOUN cana-2813 204 3 of of ADP cana-2813 204 4 cancer cancer NOUN cana-2813 204 5 exhibit exhibit NOUN cana-2813 204 6 varying vary VERB cana-2813 204 7 degrees degree NOUN cana-2813 204 8 of of ADP cana-2813 204 9 gene gene NOUN cana-2813 204 10 expression expression NOUN cana-2813 204 11 variability variability NOUN cana-2813 204 12 , , PUNCT cana-2813 204 13 which which PRON cana-2813 204 14 can can AUX cana-2813 204 15 complicate complicate VERB cana-2813 204 16 the the DET cana-2813 204 17 task task NOUN cana-2813 204 18 of of ADP cana-2813 204 19 developing develop VERB cana-2813 204 20 a a DET cana-2813 204 21 one one NUM cana-2813 204 22 - - PUNCT cana-2813 204 23 size size NOUN cana-2813 204 24 - - PUNCT cana-2813 204 25 fits fit VERB cana-2813 204 26 - - PUNCT cana-2813 204 27 all all DET cana-2813 204 28 model model NOUN cana-2813 204 29 . . PUNCT cana-2813 205 1 for for ADP cana-2813 205 2 example example NOUN cana-2813 205 3 , , PUNCT cana-2813 205 4 while while SCONJ cana-2813 205 5 dnabert dnabert PROPN cana-2813 205 6 excelled excel VERB cana-2813 205 7 at at ADP cana-2813 205 8 identifying identify VERB cana-2813 205 9 patterns pattern NOUN cana-2813 205 10 in in ADP cana-2813 205 11 relatively relatively ADV cana-2813 205 12 homogeneous homogeneous ADJ cana-2813 205 13 cancers cancer NOUN cana-2813 205 14 like like ADP cana-2813 205 15 aml aml PROPN cana-2813 205 16 & & CCONJ cana-2813 205 17 all all PRON cana-2813 205 18 , , PUNCT cana-2813 205 19 it it PRON cana-2813 205 20 faced face VERB cana-2813 205 21 more more ADV cana-2813 205 22 significant significant ADJ cana-2813 205 23 challenges challenge NOUN cana-2813 205 24 with with ADP cana-2813 205 25 cancers cancer NOUN cana-2813 205 26 like like ADP cana-2813 205 27 lung lung NOUN cana-2813 205 28 and and CCONJ cana-2813 205 29 colorectal colorectal ADJ cana-2813 205 30 cancer cancer NOUN cana-2813 205 31 , , PUNCT cana-2813 205 32 where where SCONJ cana-2813 205 33 the the DET cana-2813 205 34 gene gene NOUN cana-2813 205 35 expression expression NOUN cana-2813 205 36 profiles profile NOUN cana-2813 205 37 are be AUX cana-2813 205 38 more more ADV cana-2813 205 39 diverse diverse ADJ cana-2813 205 40 and and CCONJ cana-2813 205 41 influenced influence VERB cana-2813 205 42 by by ADP cana-2813 205 43 a a DET cana-2813 205 44 wider wide ADJ cana-2813 205 45 range range NOUN cana-2813 205 46 of of ADP cana-2813 205 47 genetic genetic ADJ cana-2813 205 48 and and CCONJ cana-2813 205 49 environmental environmental ADJ cana-2813 205 50 factors factor NOUN cana-2813 205 51 . . PUNCT cana-2813 206 1 this this DET cana-2813 206 2 heterogeneity heterogeneity NOUN cana-2813 206 3 could could AUX cana-2813 206 4 lead lead VERB cana-2813 206 5 to to ADP cana-2813 206 6 potential potential ADJ cana-2813 206 7 misclassification misclassification NOUN cana-2813 206 8 or or CCONJ cana-2813 206 9 reduced reduce VERB cana-2813 206 10 accuracy accuracy NOUN cana-2813 206 11 in in ADP cana-2813 206 12 more more ADJ cana-2813 206 13 complex complex ADJ cana-2813 206 14 cases case NOUN cana-2813 206 15 . . PUNCT cana-2813 207 1 another another DET cana-2813 207 2 critical critical ADJ cana-2813 207 3 limitation limitation NOUN cana-2813 207 4 was be AUX cana-2813 207 5 related relate VERB cana-2813 207 6 to to ADP cana-2813 207 7 the the DET cana-2813 207 8 reliance reliance NOUN cana-2813 207 9 on on ADP cana-2813 207 10 preexisting preexist VERB cana-2813 207 11 genomic genomic ADJ cana-2813 207 12 data datum NOUN cana-2813 207 13 for for ADP cana-2813 207 14 dnabert dnabert NOUN cana-2813 207 15 's 's PART cana-2813 207 16 pretraining pretraine VERB cana-2813 207 17 phase phase NOUN cana-2813 207 18 . . PUNCT cana-2813 208 1 while while SCONJ cana-2813 208 2 dnabert dnabert PROPN cana-2813 208 3 ’s ’ VERB cana-2813 208 4 pretraining pretraine VERB cana-2813 208 5 on on ADP cana-2813 208 6 largescale largescale ADJ cana-2813 208 7 genomic genomic NOUN cana-2813 208 8 sequences sequence NOUN cana-2813 208 9 provided provide VERB cana-2813 208 10 it it PRON cana-2813 208 11 with with ADP cana-2813 208 12 a a DET cana-2813 208 13 robust robust ADJ cana-2813 208 14 understanding understanding NOUN cana-2813 208 15 of of ADP cana-2813 208 16 gene gene NOUN cana-2813 208 17 relationships relationship NOUN cana-2813 208 18 , , PUNCT cana-2813 208 19 the the DET cana-2813 208 20 model model NOUN cana-2813 208 21 's 's PART cana-2813 208 22 performance performance NOUN cana-2813 208 23 is be AUX cana-2813 208 24 still still ADV cana-2813 208 25 contingent contingent ADJ cana-2813 208 26 on on ADP cana-2813 208 27 the the DET cana-2813 208 28 quality quality NOUN cana-2813 208 29 and and CCONJ cana-2813 208 30 representativeness representativeness ADJ cana-2813 208 31 of of ADP cana-2813 208 32 the the DET cana-2813 208 33 pretraining pretraine VERB cana-2813 208 34 data datum NOUN cana-2813 208 35 . . PUNCT cana-2813 209 1 if if SCONJ cana-2813 209 2 the the DET cana-2813 209 3 pretraining pretraine VERB cana-2813 209 4 data datum NOUN cana-2813 209 5 lacks lack VERB cana-2813 209 6 diversity diversity NOUN cana-2813 209 7 or or CCONJ cana-2813 209 8 is be AUX cana-2813 209 9 not not PART cana-2813 209 10 representative representative NOUN cana-2813 209 11 of of ADP cana-2813 209 12 the the DET cana-2813 209 13 specific specific ADJ cana-2813 209 14 cancer cancer NOUN cana-2813 209 15 types type NOUN cana-2813 209 16 being be AUX cana-2813 209 17 studied study VERB cana-2813 209 18 , , PUNCT cana-2813 209 19 this this PRON cana-2813 209 20 could could AUX cana-2813 209 21 lead lead VERB cana-2813 209 22 to to ADP cana-2813 209 23 biases bias NOUN cana-2813 209 24 in in ADP cana-2813 209 25 the the DET cana-2813 209 26 model model NOUN cana-2813 209 27 ’s ’s PART cana-2813 209 28 predictions prediction NOUN cana-2813 209 29 . . PUNCT cana-2813 210 1 for for ADP cana-2813 210 2 instance instance NOUN cana-2813 210 3 , , PUNCT cana-2813 210 4 if if SCONJ cana-2813 210 5 the the DET cana-2813 210 6 pretraining pretraine VERB cana-2813 210 7 data datum NOUN cana-2813 210 8 underrepresents underrepresent NOUN cana-2813 210 9 certain certain ADJ cana-2813 210 10 genetic genetic ADJ cana-2813 210 11 variants variant NOUN cana-2813 210 12 or or CCONJ cana-2813 210 13 cancer cancer NOUN cana-2813 210 14 subtypes subtype NOUN cana-2813 210 15 , , PUNCT cana-2813 210 16 dnabert dnabert NOUN cana-2813 210 17 may may AUX cana-2813 210 18 struggle struggle VERB cana-2813 210 19 to to PART cana-2813 210 20 accurately accurately ADV cana-2813 210 21 classify classify VERB cana-2813 210 22 these these DET cana-2813 210 23 cases case NOUN cana-2813 210 24 in in ADP cana-2813 210 25 the the DET cana-2813 210 26 microarray microarray NOUN cana-2813 210 27 data datum NOUN cana-2813 210 28 , , PUNCT cana-2813 210 29 leading lead VERB cana-2813 210 30 to to ADP cana-2813 210 31 potential potential ADJ cana-2813 210 32 gaps gap NOUN cana-2813 210 33 in in ADP cana-2813 210 34 its its PRON cana-2813 210 35 diagnostic diagnostic ADJ cana-2813 210 36 capability capability NOUN cana-2813 210 37 . . PUNCT cana-2813 211 1 a a DET cana-2813 211 2 b b NOUN cana-2813 211 3 c c NOUN cana-2813 211 4 fig.10 fig.10 NOUN cana-2813 211 5 : : PUNCT cana-2813 211 6 performance performance NOUN cana-2813 211 7 of of ADP cana-2813 211 8 ( ( PUNCT cana-2813 211 9 a a DET cana-2813 211 10 ) ) PUNCT cana-2813 211 11 transfer transfer NOUN cana-2813 211 12 learning learn VERB cana-2813 211 13 bert bert PROPN cana-2813 211 14 model model PROPN cana-2813 211 15 , , PUNCT cana-2813 211 16 ( ( PUNCT cana-2813 211 17 b b X cana-2813 211 18 ) ) PUNCT cana-2813 211 19 dnabert dnabert ADJ cana-2813 211 20 model model NOUN cana-2813 211 21 and and CCONJ cana-2813 211 22 ( ( PUNCT cana-2813 211 23 c c NOUN cana-2813 211 24 ) ) PUNCT cana-2813 211 25 integrated integrate VERB cana-2813 211 26 dnabert dnabert NOUN cana-2813 211 27 and and CCONJ cana-2813 211 28 mfo mfo PROPN cana-2813 211 29 model model NOUN cana-2813 211 30 on on ADP cana-2813 211 31 all all DET cana-2813 211 32 and and CCONJ cana-2813 211 33 aml aml NOUN cana-2813 211 34 lymphoma lymphoma NOUN cana-2813 211 35 gene gene NOUN cana-2813 211 36 expression expression NOUN cana-2813 211 37 microarrays microarray VERB cana-2813 211 38 communications communication NOUN cana-2813 211 39 on on ADP cana-2813 211 40 applied apply VERB cana-2813 211 41 nonlinear nonlinear ADJ cana-2813 211 42 analysis analysis NOUN cana-2813 211 43 issn issn NOUN cana-2813 211 44 : : PUNCT cana-2813 211 45 1074 1074 NUM cana-2813 211 46 - - PUNCT cana-2813 211 47 133x 133x NUM cana-2813 211 48 vol vol NOUN cana-2813 211 49 32 32 NUM cana-2813 211 50 no no NOUN cana-2813 211 51 . . PUNCT cana-2813 212 1 4s 4s NUM cana-2813 212 2 ( ( PUNCT cana-2813 212 3 2025 2025 NUM cana-2813 212 4 ) ) PUNCT cana-2813 212 5 285 285 NUM cana-2813 212 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 212 7 table.6 table.6 NOUN cana-2813 212 8 : : PUNCT cana-2813 212 9 summary summary NOUN cana-2813 212 10 of of ADP cana-2813 212 11 a a DET cana-2813 212 12 ) ) PUNCT cana-2813 212 13 bert bert PROPN cana-2813 212 14 , , PUNCT cana-2813 212 15 b b NOUN cana-2813 212 16 ) ) PUNCT cana-2813 212 17 dnabert dnabert NOUN cana-2813 212 18 and and CCONJ cana-2813 212 19 c c NOUN cana-2813 212 20 ) ) PUNCT cana-2813 212 21 integrated integrate VERB cana-2813 212 22 model model NOUN cana-2813 212 23 performance performance NOUN cana-2813 212 24 on on ADP cana-2813 212 25 all all DET cana-2813 212 26 and and CCONJ cana-2813 212 27 aml aml NOUN cana-2813 212 28 lymphoma lymphoma NOUN cana-2813 212 29 dataset dataset VERB cana-2813 212 30 a a DET cana-2813 212 31 ) ) PUNCT cana-2813 212 32 bert bert PROPN cana-2813 212 33 index index NOUN cana-2813 212 34 precision precision NOUN cana-2813 212 35 recall recall VERB cana-2813 212 36 f1 f1 NOUN cana-2813 212 37 - - PUNCT cana-2813 212 38 score score NOUN cana-2813 212 39 support support NOUN cana-2813 212 40 all all DET cana-2813 212 41 0.75 0.75 NUM cana-2813 212 42 0.9 0.9 NUM cana-2813 212 43 0.8181 0.8181 NUM cana-2813 212 44 20.0 20.0 NUM cana-2813 212 45 aml aml NOUN cana-2813 213 1 0.8 0.8 NUM cana-2813 213 2 0.5714 0.5714 NUM cana-2813 213 3 0.6666 0.6666 NUM cana-2813 213 4 14.0 14.0 NUM cana-2813 213 5 accuracy accuracy NOUN cana-2813 213 6 0.7647 0.7647 NUM cana-2813 213 7 0.7647 0.7647 NUM cana-2813 213 8 0.7647 0.7647 NUM cana-2813 213 9 0.7647 0.7647 NUM cana-2813 213 10 macro macro NOUN cana-2813 213 11 avg avg PROPN cana-2813 213 12 0.775 0.775 NUM cana-2813 213 13 0.7357 0.7357 NUM cana-2813 213 14 0.7424 0.7424 NUM cana-2813 213 15 34.0 34.0 NUM cana-2813 213 16 weighted weight VERB cana-2813 213 17 avg avg NOUN cana-2813 213 18 0.7705 0.7705 NUM cana-2813 213 19 0.7647 0.7647 NUM cana-2813 213 20 0.7557 0.7557 NUM cana-2813 213 21 34.0 34.0 NUM cana-2813 213 22 b b NOUN cana-2813 213 23 ) ) PUNCT cana-2813 213 24 dnabert dnabert ADJ cana-2813 213 25 index index NOUN cana-2813 213 26 precision precision NOUN cana-2813 213 27 recall recall VERB cana-2813 213 28 f1 f1 NOUN cana-2813 213 29 - - PUNCT cana-2813 213 30 score score NOUN cana-2813 213 31 support support NOUN cana-2813 213 32 all all DET cana-2813 213 33 0.9473 0.9473 NUM cana-2813 213 34 0.90 0.90 NUM cana-2813 213 35 0.9230 0.9230 NUM cana-2813 213 36 20.0 20.0 NUM cana-2813 213 37 aml aml NOUN cana-2813 213 38 0.8666 0.8666 NUM cana-2813 213 39 0.9285 0.9285 NUM cana-2813 213 40 0.8965 0.8965 NUM cana-2813 213 41 14.0 14.0 NUM cana-2813 213 42 accuracy accuracy NOUN cana-2813 213 43 0.9117 0.9117 NUM cana-2813 213 44 0.9117 0.9117 NUM cana-2813 213 45 0.9117 0.9117 NUM cana-2813 213 46 0.9117 0.9117 NUM cana-2813 213 47 macro macro NOUN cana-2813 213 48 avg avg NOUN cana-2813 213 49 0.9070 0.9070 NUM cana-2813 213 50 0.9142 0.9142 NUM cana-2813 213 51 0.9098 0.9098 NUM cana-2813 213 52 34.0 34.0 NUM cana-2813 213 53 weighted weight VERB cana-2813 213 54 avg avg NOUN cana-2813 213 55 0.9141 0.9141 NUM cana-2813 213 56 0.9117 0.9117 NUM cana-2813 213 57 0.9121 0.9121 NUM cana-2813 213 58 34.0 34.0 NUM cana-2813 213 59 c c NOUN cana-2813 213 60 ) ) PUNCT cana-2813 213 61 integrated integrate VERB cana-2813 213 62 dnabert dnabert PROPN cana-2813 213 63 & & CCONJ cana-2813 213 64 mfo mfo PROPN cana-2813 213 65 index index PROPN cana-2813 213 66 precision precision NOUN cana-2813 213 67 recall recall VERB cana-2813 213 68 f1 f1 NOUN cana-2813 213 69 - - PUNCT cana-2813 213 70 score score NOUN cana-2813 213 71 support support NOUN cana-2813 213 72 all all DET cana-2813 213 73 0.9523 0.9523 NUM cana-2813 213 74 1.0 1.0 NUM cana-2813 213 75 0.975610 0.975610 NUM cana-2813 213 76 20.0 20.0 NUM cana-2813 213 77 aml aml NOUN cana-2813 213 78 1.0 1.0 NUM cana-2813 213 79 0.9285 0.9285 NUM cana-2813 213 80 0.962963 0.962963 NUM cana-2813 213 81 14.0 14.0 NUM cana-2813 213 82 accuracy accuracy NOUN cana-2813 213 83 0.9705 0.9705 NUM cana-2813 213 84 0.9705 0.9705 NUM cana-2813 213 85 0.970588 0.970588 NUM cana-2813 213 86 0.9705 0.9705 NUM cana-2813 213 87 macro macro ADJ cana-2813 213 88 avg avg NOUN cana-2813 213 89 0.9761 0.9761 NUM cana-2813 213 90 0.9642 0.9642 NUM cana-2813 213 91 0.969286 0.969286 NUM cana-2813 213 92 34.0 34.0 NUM cana-2813 213 93 weighted weight VERB cana-2813 213 94 avg avg NOUN cana-2813 213 95 0.9719 0.9719 NUM cana-2813 213 96 0.9705 0.9705 NUM cana-2813 213 97 0.970402 0.970402 NUM cana-2813 213 98 34.0 34.0 NUM cana-2813 213 99 moreover moreover ADV cana-2813 213 100 , , PUNCT cana-2813 213 101 the the DET cana-2813 213 102 application application NOUN cana-2813 213 103 of of ADP cana-2813 213 104 mfo mfo PROPN cana-2813 213 105 , , PUNCT cana-2813 213 106 while while SCONJ cana-2813 213 107 effective effective ADJ cana-2813 213 108 in in ADP cana-2813 213 109 improving improve VERB cana-2813 213 110 model model NOUN cana-2813 213 111 performance performance NOUN cana-2813 213 112 , , PUNCT cana-2813 213 113 also also ADV cana-2813 213 114 introduced introduce VERB cana-2813 213 115 additional additional ADJ cana-2813 213 116 computational computational ADJ cana-2813 213 117 complexity complexity NOUN cana-2813 213 118 . . PUNCT cana-2813 214 1 metaheuristic metaheuristic ADJ cana-2813 214 2 algorithms algorithm NOUN cana-2813 214 3 like like ADP cana-2813 214 4 mfo mfo PROPN cana-2813 214 5 require require VERB cana-2813 214 6 substantial substantial ADJ cana-2813 214 7 computational computational ADJ cana-2813 214 8 resources resource NOUN cana-2813 214 9 , , PUNCT cana-2813 214 10 particularly particularly ADV cana-2813 214 11 when when SCONJ cana-2813 214 12 dealing deal VERB cana-2813 214 13 with with ADP cana-2813 214 14 high high ADJ cana-2813 214 15 - - PUNCT cana-2813 214 16 dimensional dimensional ADJ cana-2813 214 17 data datum NOUN cana-2813 214 18 and and CCONJ cana-2813 214 19 complex complex ADJ cana-2813 214 20 models model NOUN cana-2813 214 21 like like ADP cana-2813 214 22 dnabert dnabert NOUN cana-2813 214 23 . . PUNCT cana-2813 215 1 the the DET cana-2813 215 2 iterative iterative ADJ cana-2813 215 3 nature nature NOUN cana-2813 215 4 of of ADP cana-2813 215 5 mfo mfo PROPN cana-2813 215 6 , , PUNCT cana-2813 215 7 which which PRON cana-2813 215 8 involves involve VERB cana-2813 215 9 evaluating evaluate VERB cana-2813 215 10 multiple multiple ADJ cana-2813 215 11 candidate candidate NOUN cana-2813 215 12 solutions solution NOUN cana-2813 215 13 across across ADP cana-2813 215 14 several several ADJ cana-2813 215 15 iterations iteration NOUN cana-2813 215 16 , , PUNCT cana-2813 215 17 can can AUX cana-2813 215 18 lead lead VERB cana-2813 215 19 to to ADP cana-2813 215 20 longer long ADV cana-2813 215 21 training training NOUN cana-2813 215 22 times time NOUN cana-2813 215 23 and and CCONJ cana-2813 215 24 increased increase VERB cana-2813 215 25 computational computational ADJ cana-2813 215 26 costs cost NOUN cana-2813 215 27 . . PUNCT cana-2813 216 1 this this DET cana-2813 216 2 limitation limitation NOUN cana-2813 216 3 is be AUX cana-2813 216 4 particularly particularly ADV cana-2813 216 5 relevant relevant ADJ cana-2813 216 6 in in ADP cana-2813 216 7 a a DET cana-2813 216 8 clinical clinical ADJ cana-2813 216 9 setting setting NOUN cana-2813 216 10 , , PUNCT cana-2813 216 11 where where SCONJ cana-2813 216 12 time time NOUN cana-2813 216 13 and and CCONJ cana-2813 216 14 resource resource NOUN cana-2813 216 15 constraints constraint NOUN cana-2813 216 16 may may AUX cana-2813 216 17 limit limit VERB cana-2813 216 18 the the DET cana-2813 216 19 feasibility feasibility NOUN cana-2813 216 20 of of ADP cana-2813 216 21 deploying deploy VERB cana-2813 216 22 such such ADJ cana-2813 216 23 computationally computationally ADV cana-2813 216 24 intensive intensive ADJ cana-2813 216 25 models model NOUN cana-2813 216 26 . . PUNCT cana-2813 217 1 the the DET cana-2813 217 2 generalizability generalizability NOUN cana-2813 217 3 of of ADP cana-2813 217 4 the the DET cana-2813 217 5 dnabert dnabert PROPN cana-2813 217 6 - - PUNCT cana-2813 217 7 mfo mfo PROPN cana-2813 217 8 model model NOUN cana-2813 217 9 is be AUX cana-2813 217 10 another another DET cana-2813 217 11 critical critical ADJ cana-2813 217 12 area area NOUN cana-2813 217 13 of of ADP cana-2813 217 14 discussion discussion NOUN cana-2813 217 15 . . PUNCT cana-2813 218 1 while while SCONJ cana-2813 218 2 the the DET cana-2813 218 3 model model NOUN cana-2813 218 4 demonstrated demonstrate VERB cana-2813 218 5 high high ADJ cana-2813 218 6 accuracy accuracy NOUN cana-2813 218 7 across across ADP cana-2813 218 8 multiple multiple ADJ cana-2813 218 9 cancer cancer NOUN cana-2813 218 10 types type NOUN cana-2813 218 11 in in ADP cana-2813 218 12 this this DET cana-2813 218 13 study study NOUN cana-2813 218 14 , , PUNCT cana-2813 218 15 its its PRON cana-2813 218 16 generalizability generalizability NOUN cana-2813 218 17 to to ADP cana-2813 218 18 other other ADJ cana-2813 218 19 cancers cancer NOUN cana-2813 218 20 or or CCONJ cana-2813 218 21 diseases disease NOUN cana-2813 218 22 remains remain VERB cana-2813 218 23 an an DET cana-2813 218 24 open open ADJ cana-2813 218 25 question question NOUN cana-2813 218 26 . . PUNCT cana-2813 219 1 microarray microarray NOUN cana-2813 219 2 gene gene NOUN cana-2813 219 3 expression expression NOUN cana-2813 219 4 data datum NOUN cana-2813 219 5 can can AUX cana-2813 219 6 vary vary VERB cana-2813 219 7 significantly significantly ADV cana-2813 219 8 between between ADP cana-2813 219 9 different different ADJ cana-2813 219 10 datasets dataset NOUN cana-2813 219 11 , , PUNCT cana-2813 219 12 even even ADV cana-2813 219 13 for for ADP cana-2813 219 14 the the DET cana-2813 219 15 same same ADJ cana-2813 219 16 type type NOUN cana-2813 219 17 of of ADP cana-2813 219 18 cancer cancer NOUN cana-2813 219 19 , , PUNCT cana-2813 219 20 due due ADP cana-2813 219 21 to to ADP cana-2813 219 22 factors factor NOUN cana-2813 219 23 such such ADJ cana-2813 219 24 as as ADP cana-2813 219 25 differences difference NOUN cana-2813 219 26 in in ADP cana-2813 219 27 sample sample NOUN cana-2813 219 28 collection collection NOUN cana-2813 219 29 , , PUNCT cana-2813 219 30 preprocessing preprocesse VERB cana-2813 219 31 techniques technique NOUN cana-2813 219 32 , , PUNCT cana-2813 219 33 and and CCONJ cana-2813 219 34 patient patient ADJ cana-2813 219 35 demographics demographic NOUN cana-2813 219 36 . . PUNCT cana-2813 220 1 therefore therefore ADV cana-2813 220 2 , , PUNCT cana-2813 220 3 while while SCONJ cana-2813 220 4 the the DET cana-2813 220 5 dnabertmfo dnabertmfo NOUN cana-2813 220 6 model model NOUN cana-2813 220 7 performed perform VERB cana-2813 220 8 well well ADV cana-2813 220 9 on on ADP cana-2813 220 10 the the DET cana-2813 220 11 datasets dataset NOUN cana-2813 220 12 used use VERB cana-2813 220 13 in in ADP cana-2813 220 14 this this DET cana-2813 220 15 study study NOUN cana-2813 220 16 , , PUNCT cana-2813 220 17 its its PRON cana-2813 220 18 performance performance NOUN cana-2813 220 19 on on ADP cana-2813 220 20 external external ADJ cana-2813 220 21 datasets dataset NOUN cana-2813 220 22 or or CCONJ cana-2813 220 23 in in ADP cana-2813 220 24 a a DET cana-2813 220 25 real real ADJ cana-2813 220 26 - - PUNCT cana-2813 220 27 world world NOUN cana-2813 220 28 clinical clinical ADJ cana-2813 220 29 setting setting NOUN cana-2813 220 30 needs need NOUN cana-2813 220 31 to to PART cana-2813 220 32 be be AUX cana-2813 220 33 carefully carefully ADV cana-2813 220 34 evaluated evaluate VERB cana-2813 220 35 . . PUNCT cana-2813 221 1 in in ADP cana-2813 221 2 clinical clinical ADJ cana-2813 221 3 applications application NOUN cana-2813 221 4 , , PUNCT cana-2813 221 5 model model NOUN cana-2813 221 6 interpretability interpretability NOUN cana-2813 221 7 is be AUX cana-2813 221 8 paramount paramount ADJ cana-2813 221 9 , , PUNCT cana-2813 221 10 particularly particularly ADV cana-2813 221 11 in in ADP cana-2813 221 12 the the DET cana-2813 221 13 context context NOUN cana-2813 221 14 of of ADP cana-2813 221 15 cancer cancer NOUN cana-2813 221 16 diagnosis diagnosis NOUN cana-2813 221 17 , , PUNCT cana-2813 221 18 where where SCONJ cana-2813 221 19 decisions decision NOUN cana-2813 221 20 based base VERB cana-2813 221 21 on on ADP cana-2813 221 22 model model NOUN cana-2813 221 23 predictions prediction NOUN cana-2813 221 24 can can AUX cana-2813 221 25 have have VERB cana-2813 221 26 significant significant ADJ cana-2813 221 27 implications implication NOUN cana-2813 221 28 for for ADP cana-2813 221 29 patient patient ADJ cana-2813 221 30 communications communication NOUN cana-2813 221 31 on on ADP cana-2813 221 32 applied apply VERB cana-2813 221 33 nonlinear nonlinear ADJ cana-2813 221 34 analysis analysis NOUN cana-2813 221 35 issn issn NOUN cana-2813 221 36 : : PUNCT cana-2813 221 37 1074 1074 NUM cana-2813 221 38 - - PUNCT cana-2813 221 39 133x 133x NUM cana-2813 221 40 vol vol NOUN cana-2813 221 41 32 32 NUM cana-2813 221 42 no no NOUN cana-2813 221 43 . . PUNCT cana-2813 222 1 4s 4s NUM cana-2813 222 2 ( ( PUNCT cana-2813 222 3 2025 2025 NUM cana-2813 222 4 ) ) PUNCT cana-2813 222 5 286 286 NUM cana-2813 222 6 https://internationalpubls.com https://internationalpubls.com NUM cana-2813 222 7 care care NOUN cana-2813 222 8 . . PUNCT cana-2813 223 1 while while SCONJ cana-2813 223 2 dnabert dnabert PROPN cana-2813 223 3 and and CCONJ cana-2813 223 4 mfo mfo PROPN cana-2813 223 5 provided provide VERB cana-2813 223 6 high high ADJ cana-2813 223 7 accuracy accuracy NOUN cana-2813 223 8 , , PUNCT cana-2813 223 9 the the DET cana-2813 223 10 black black ADJ cana-2813 223 11 - - PUNCT cana-2813 223 12 box box NOUN cana-2813 223 13 nature nature NOUN cana-2813 223 14 of of ADP cana-2813 223 15 deep deep ADJ cana-2813 223 16 learning learning NOUN cana-2813 223 17 models model NOUN cana-2813 223 18 and and CCONJ cana-2813 223 19 the the DET cana-2813 223 20 complexity complexity NOUN cana-2813 223 21 of of ADP cana-2813 223 22 metaheuristic metaheuristic ADJ cana-2813 223 23 optimization optimization NOUN cana-2813 223 24 algorithms algorithm NOUN cana-2813 223 25 can can AUX cana-2813 223 26 make make VERB cana-2813 223 27 it it PRON cana-2813 223 28 challenging challenging ADJ cana-2813 223 29 to to PART cana-2813 223 30 interpret interpret VERB cana-2813 223 31 the the DET cana-2813 223 32 results result NOUN cana-2813 223 33 . . PUNCT cana-2813 224 1 clinicians clinician NOUN cana-2813 224 2 may may AUX cana-2813 224 3 be be AUX cana-2813 224 4 uncertain uncertain ADJ cana-2813 224 5 to to PART cana-2813 224 6 rely rely VERB cana-2813 224 7 on on ADP cana-2813 224 8 a a DET cana-2813 224 9 model model NOUN cana-2813 224 10 's 's PART cana-2813 224 11 estimates estimate NOUN cana-2813 224 12 without without ADP cana-2813 224 13 a a DET cana-2813 224 14 clear clear ADJ cana-2813 224 15 understanding understanding NOUN cana-2813 224 16 of of ADP cana-2813 224 17 the the DET cana-2813 224 18 underlying underlie VERB cana-2813 224 19 decision decision NOUN cana-2813 224 20 - - PUNCT cana-2813 224 21 making make VERB cana-2813 224 22 process process NOUN cana-2813 224 23 , , PUNCT cana-2813 224 24 particularly particularly ADV cana-2813 224 25 when when SCONJ cana-2813 224 26 it it PRON cana-2813 224 27 comes come VERB cana-2813 224 28 to to ADP cana-2813 224 29 selecting select VERB cana-2813 224 30 treatment treatment NOUN cana-2813 224 31 options option NOUN cana-2813 224 32 or or CCONJ cana-2813 224 33 making make VERB cana-2813 224 34 critical critical ADJ cana-2813 224 35 diagnostic diagnostic ADJ cana-2813 224 36 decisions decision NOUN cana-2813 224 37 . . PUNCT cana-2813 225 1 therefore therefore ADV cana-2813 225 2 , , PUNCT cana-2813 225 3 developing develop VERB cana-2813 225 4 methods method NOUN cana-2813 225 5 to to PART cana-2813 225 6 improve improve VERB cana-2813 225 7 the the DET cana-2813 225 8 interpretability interpretability NOUN cana-2813 225 9 of of ADP cana-2813 225 10 the the DET cana-2813 225 11 dnabert dnabert PROPN cana-2813 225 12 - - PUNCT cana-2813 225 13 mfo mfo PROPN cana-2813 225 14 model model NOUN cana-2813 225 15 , , PUNCT cana-2813 225 16 such such ADJ cana-2813 225 17 as as ADP cana-2813 225 18 feature feature NOUN cana-2813 225 19 importance importance NOUN cana-2813 225 20 analysis analysis NOUN cana-2813 225 21 or or CCONJ cana-2813 225 22 decisionpath decisionpath NOUN cana-2813 225 23 visualization visualization NOUN cana-2813 225 24 , , PUNCT cana-2813 225 25 could could AUX cana-2813 225 26 be be AUX cana-2813 225 27 crucial crucial ADJ cana-2813 225 28 for for ADP cana-2813 225 29 its its PRON cana-2813 225 30 clinical clinical ADJ cana-2813 225 31 adoption adoption NOUN cana-2813 225 32 . . PUNCT cana-2813 226 1 another another DET cana-2813 226 2 important important ADJ cana-2813 226 3 aspect aspect NOUN cana-2813 226 4 to to PART cana-2813 226 5 consider consider VERB cana-2813 226 6 is be AUX cana-2813 226 7 the the DET cana-2813 226 8 potential potential NOUN cana-2813 226 9 for for ADP cana-2813 226 10 biases bias NOUN cana-2813 226 11 in in ADP cana-2813 226 12 the the DET cana-2813 226 13 model model NOUN cana-2813 226 14 . . PUNCT cana-2813 227 1 the the DET cana-2813 227 2 training training NOUN cana-2813 227 3 data datum NOUN cana-2813 227 4 used use VERB cana-2813 227 5 to to ADP cana-2813 227 6 fine fine ADJ cana-2813 227 7 - - PUNCT cana-2813 227 8 tune tune NOUN cana-2813 227 9 dnabert dnabert NOUN cana-2813 227 10 and and CCONJ cana-2813 227 11 optimize optimize NOUN cana-2813 227 12 mfo mfo NOUN cana-2813 227 13 can can AUX cana-2813 227 14 introduce introduce VERB cana-2813 227 15 biases bias NOUN cana-2813 227 16 if if SCONJ cana-2813 227 17 not not PART cana-2813 227 18 carefully carefully ADV cana-2813 227 19 curated curate VERB cana-2813 227 20 . . PUNCT cana-2813 228 1 for for ADP cana-2813 228 2 example example NOUN cana-2813 228 3 , , PUNCT cana-2813 228 4 if if SCONJ cana-2813 228 5 the the DET cana-2813 228 6 training training NOUN cana-2813 228 7 data data NOUN cana-2813 228 8 overrepresents overrepresent VERB cana-2813 228 9 certain certain ADJ cana-2813 228 10 populations population NOUN cana-2813 228 11 ( ( PUNCT cana-2813 228 12 e.g. e.g. ADV cana-2813 228 13 , , PUNCT cana-2813 228 14 specific specific ADJ cana-2813 228 15 ethnic ethnic ADJ cana-2813 228 16 groups group NOUN cana-2813 228 17 or or CCONJ cana-2813 228 18 geographic geographic ADJ cana-2813 228 19 regions region NOUN cana-2813 228 20 ) ) PUNCT cana-2813 228 21 , , PUNCT cana-2813 228 22 the the DET cana-2813 228 23 model model NOUN cana-2813 228 24 may may AUX cana-2813 228 25 develop develop VERB cana-2813 228 26 biases bias NOUN cana-2813 228 27 that that PRON cana-2813 228 28 affect affect VERB cana-2813 228 29 its its PRON cana-2813 228 30 performance performance NOUN cana-2813 228 31 on on ADP cana-2813 228 32 underrepresented underrepresented ADJ cana-2813 228 33 populations population NOUN cana-2813 228 34 . . PUNCT cana-2813 229 1 this this PRON cana-2813 229 2 could could AUX cana-2813 229 3 lead lead VERB cana-2813 229 4 to to ADP cana-2813 229 5 differences difference NOUN cana-2813 229 6 in in ADP cana-2813 229 7 diagnostic diagnostic ADJ cana-2813 229 8 accuracy accuracy NOUN cana-2813 229 9 , , PUNCT cana-2813 229 10 potentially potentially ADV cana-2813 229 11 exacerbating exacerbate VERB cana-2813 229 12 existing exist VERB cana-2813 229 13 health health NOUN cana-2813 229 14 inequities inequity NOUN cana-2813 229 15 . . PUNCT cana-2813 230 1 addressing address VERB cana-2813 230 2 these these DET cana-2813 230 3 partialities partiality NOUN cana-2813 230 4 requires require VERB cana-2813 230 5 careful careful ADJ cana-2813 230 6 dataset dataset NOUN cana-2813 230 7 curation curation NOUN cana-2813 230 8 and and CCONJ cana-2813 230 9 potentially potentially ADV cana-2813 230 10 the the DET cana-2813 230 11 use use NOUN cana-2813 230 12 of of ADP cana-2813 230 13 fairness fairness NOUN cana-2813 230 14 - - PUNCT cana-2813 230 15 aware aware ADJ cana-2813 230 16 algorithms algorithm NOUN cana-2813 230 17 that that PRON cana-2813 230 18 can can AUX cana-2813 230 19 mitigate mitigate VERB cana-2813 230 20 the the DET cana-2813 230 21 impact impact NOUN cana-2813 230 22 of of ADP cana-2813 230 23 biased biased ADJ cana-2813 230 24 data datum NOUN cana-2813 230 25 . . PUNCT cana-2813 231 1 ethical ethical ADJ cana-2813 231 2 considerations consideration NOUN cana-2813 231 3 also also ADV cana-2813 231 4 extend extend VERB cana-2813 231 5 to to ADP cana-2813 231 6 the the DET cana-2813 231 7 deployment deployment NOUN cana-2813 231 8 of of ADP cana-2813 231 9 such such ADJ cana-2813 231 10 models model NOUN cana-2813 231 11 in in ADP cana-2813 231 12 clinical clinical ADJ cana-2813 231 13 settings setting NOUN cana-2813 231 14 . . PUNCT cana-2813 232 1 the the DET cana-2813 232 2 use use NOUN cana-2813 232 3 of of ADP cana-2813 232 4 ai ai NOUN cana-2813 232 5 in in ADP cana-2813 232 6 healthcare healthcare NOUN cana-2813 232 7 raises raise VERB cana-2813 232 8 important important ADJ cana-2813 232 9 questions question NOUN cana-2813 232 10 about about ADP cana-2813 232 11 the the DET cana-2813 232 12 transparency transparency NOUN cana-2813 232 13 of of ADP cana-2813 232 14 decision decision NOUN cana-2813 232 15 - - PUNCT cana-2813 232 16 making making NOUN cana-2813 232 17 , , PUNCT cana-2813 232 18 patient patient ADJ cana-2813 232 19 consent consent NOUN cana-2813 232 20 , , PUNCT cana-2813 232 21 and and CCONJ cana-2813 232 22 the the DET cana-2813 232 23 potential potential NOUN cana-2813 232 24 for for ADP cana-2813 232 25 ai ai NOUN cana-2813 232 26 to to ADP cana-2813 232 27 either either CCONJ cana-2813 232 28 complement complement VERB cana-2813 232 29 or or CCONJ cana-2813 232 30 replace replace VERB cana-2813 232 31 human human ADJ cana-2813 232 32 judgment judgment NOUN cana-2813 232 33 . . PUNCT cana-2813 233 1 while while SCONJ cana-2813 233 2 the the DET cana-2813 233 3 dnabert dnabert PROPN cana-2813 233 4 - - PUNCT cana-2813 233 5 mfo mfo PROPN cana-2813 233 6 model model NOUN cana-2813 233 7 offers offer VERB cana-2813 233 8 significant significant ADJ cana-2813 233 9 potential potential NOUN cana-2813 233 10 for for ADP cana-2813 233 11 improving improve VERB cana-2813 233 12 cancer cancer NOUN cana-2813 233 13 diagnosis diagnosis NOUN cana-2813 233 14 , , PUNCT cana-2813 233 15 it it PRON cana-2813 233 16 is be AUX cana-2813 233 17 essential essential ADJ cana-2813 233 18 to to PART cana-2813 233 19 ensure ensure VERB cana-2813 233 20 that that SCONJ cana-2813 233 21 its its PRON cana-2813 233 22 deployment deployment NOUN cana-2813 233 23 is be AUX cana-2813 233 24 guided guide VERB cana-2813 233 25 by by ADP cana-2813 233 26 ethical ethical ADJ cana-2813 233 27 principles principle NOUN cana-2813 233 28 that that PRON cana-2813 233 29 prioritize prioritize VERB cana-2813 233 30 patient patient ADJ cana-2813 233 31 safety safety NOUN cana-2813 233 32 , , PUNCT cana-2813 233 33 autonomy autonomy NOUN cana-2813 233 34 , , PUNCT cana-2813 233 35 and and CCONJ cana-2813 233 36 equity equity NOUN cana-2813 233 37 . . PUNCT cana-2813 234 1 this this PRON cana-2813 234 2 includes include VERB cana-2813 234 3 ensuring ensure VERB cana-2813 234 4 that that SCONJ cana-2813 234 5 the the DET cana-2813 234 6 model model NOUN cana-2813 234 7 's 's PART cana-2813 234 8 predictions prediction NOUN cana-2813 234 9 are be AUX cana-2813 234 10 used use VERB cana-2813 234 11 to to PART cana-2813 234 12 support support VERB cana-2813 234 13 , , PUNCT cana-2813 234 14 rather rather ADV cana-2813 234 15 than than ADP cana-2813 234 16 replace replace VERB cana-2813 234 17 , , PUNCT cana-2813 234 18 clinical clinical ADJ cana-2813 234 19 decisionmaking decisionmaking NOUN cana-2813 234 20 , , PUNCT cana-2813 234 21 and and CCONJ cana-2813 234 22 that that SCONJ cana-2813 234 23 patients patient NOUN cana-2813 234 24 are be AUX cana-2813 234 25 fully fully ADV cana-2813 234 26 informed inform VERB cana-2813 234 27 about about ADP cana-2813 234 28 how how SCONJ cana-2813 234 29 ai ai VERB cana-2813 234 30 is be AUX cana-2813 234 31 being be AUX cana-2813 234 32 used use VERB cana-2813 234 33 in in ADP cana-2813 234 34 their their PRON cana-2813 234 35 care care NOUN cana-2813 234 36 . . PUNCT cana-2813 235 1 the the DET cana-2813 235 2 findings finding NOUN cana-2813 235 3 from from ADP cana-2813 235 4 this this DET cana-2813 235 5 research research NOUN cana-2813 235 6 suggest suggest VERB cana-2813 235 7 several several ADJ cana-2813 235 8 avenues avenue NOUN cana-2813 235 9 for for ADP cana-2813 235 10 future future ADJ cana-2813 235 11 work work NOUN cana-2813 235 12 . . PUNCT cana-2813 236 1 one one NUM cana-2813 236 2 potential potential ADJ cana-2813 236 3 route route NOUN cana-2813 236 4 is be AUX cana-2813 236 5 the the DET cana-2813 236 6 development development NOUN cana-2813 236 7 of of ADP cana-2813 236 8 hybrid hybrid ADJ cana-2813 236 9 models model NOUN cana-2813 236 10 that that PRON cana-2813 236 11 combine combine VERB cana-2813 236 12 the the DET cana-2813 236 13 strengths strength NOUN cana-2813 236 14 of of ADP cana-2813 236 15 dnabert dnabert NOUN cana-2813 236 16 and and CCONJ cana-2813 236 17 mfo mfo NOUN cana-2813 236 18 with with ADP cana-2813 236 19 other other ADJ cana-2813 236 20 machine machine NOUN cana-2813 236 21 learning learning NOUN cana-2813 236 22 or or CCONJ cana-2813 236 23 statistical statistical ADJ cana-2813 236 24 methods method NOUN cana-2813 236 25 . . PUNCT cana-2813 237 1 for for ADP cana-2813 237 2 example example NOUN cana-2813 237 3 , , PUNCT cana-2813 237 4 integrating integrate VERB cana-2813 237 5 the the DET cana-2813 237 6 dnabert dnabert ADJ cana-2813 237 7 - - PUNCT cana-2813 237 8 mfo mfo NOUN cana-2813 237 9 framework framework NOUN cana-2813 237 10 with with ADP cana-2813 237 11 ensemble ensemble ADJ cana-2813 237 12 methods method NOUN cana-2813 237 13 or or CCONJ cana-2813 237 14 incorporating incorporate VERB cana-2813 237 15 additional additional ADJ cana-2813 237 16 layers layer NOUN cana-2813 237 17 of of ADP cana-2813 237 18 feature feature NOUN cana-2813 237 19 selection selection NOUN cana-2813 237 20 could could AUX cana-2813 237 21 further far ADV cana-2813 237 22 enhance enhance VERB cana-2813 237 23 model model NOUN cana-2813 237 24 performance performance NOUN cana-2813 237 25 and and CCONJ cana-2813 237 26 generalizability generalizability NOUN cana-2813 237 27 . . PUNCT cana-2813 238 1 another another DET cana-2813 238 2 area area NOUN cana-2813 238 3 for for ADP cana-2813 238 4 exploration exploration NOUN cana-2813 238 5 is be AUX cana-2813 238 6 the the DET cana-2813 238 7 use use NOUN cana-2813 238 8 of of ADP cana-2813 238 9 explainable explainable ADJ cana-2813 238 10 ai ai NOUN cana-2813 238 11 techniques technique NOUN cana-2813 238 12 to to PART cana-2813 238 13 improve improve VERB cana-2813 238 14 the the DET cana-2813 238 15 interpretability interpretability NOUN cana-2813 238 16 of of ADP cana-2813 238 17 the the DET cana-2813 238 18 dnabert dnabert PROPN cana-2813 238 19 - - PUNCT cana-2813 238 20 mfo mfo PROPN cana-2813 238 21 model model NOUN cana-2813 238 22 , , PUNCT cana-2813 238 23 making make VERB cana-2813 238 24 it it PRON cana-2813 238 25 more more ADV cana-2813 238 26 accessible accessible ADJ cana-2813 238 27 and and CCONJ cana-2813 238 28 trustworthy trustworthy ADJ cana-2813 238 29 for for ADP cana-2813 238 30 clinical clinical ADJ cana-2813 238 31 use use NOUN cana-2813 238 32 . . PUNCT cana-2813 239 1 additionally additionally ADV cana-2813 239 2 , , PUNCT cana-2813 239 3 further further ADJ cana-2813 239 4 research research NOUN cana-2813 239 5 is be AUX cana-2813 239 6 needed need VERB cana-2813 239 7 to to PART cana-2813 239 8 explore explore VERB cana-2813 239 9 the the DET cana-2813 239 10 application application NOUN cana-2813 239 11 of of ADP cana-2813 239 12 the the DET cana-2813 239 13 dnabert dnabert PROPN cana-2813 239 14 - - PUNCT cana-2813 239 15 mfo mfo NOUN cana-2813 239 16 model model NOUN cana-2813 239 17 to to ADP cana-2813 239 18 other other ADJ cana-2813 239 19 types type NOUN cana-2813 239 20 of of ADP cana-2813 239 21 omics omics PROPN cana-2813 239 22 data datum NOUN cana-2813 239 23 , , PUNCT cana-2813 239 24 such such ADJ cana-2813 239 25 as as ADP cana-2813 239 26 rna rna NOUN cana-2813 239 27 - - PUNCT cana-2813 239 28 seq seq NOUN cana-2813 239 29 or or CCONJ cana-2813 239 30 proteomics proteomic NOUN cana-2813 239 31 data datum NOUN cana-2813 239 32 , , PUNCT cana-2813 239 33 which which PRON cana-2813 239 34 may may AUX cana-2813 239 35 provide provide VERB cana-2813 239 36 complementary complementary ADJ cana-2813 239 37 information information NOUN cana-2813 239 38 to to PART cana-2813 239 39 gene gene VERB cana-2813 239 40 expression expression NOUN cana-2813 239 41 data datum NOUN cana-2813 239 42 and and CCONJ cana-2813 239 43 enhance enhance VERB cana-2813 239 44 the the DET cana-2813 239 45 model model NOUN cana-2813 239 46 ’s ’s PART cana-2813 239 47 diagnostic diagnostic ADJ cana-2813 239 48 capabilities capability NOUN cana-2813 239 49 . . PUNCT cana-2813 240 1 expanding expand VERB cana-2813 240 2 the the DET cana-2813 240 3 model model NOUN cana-2813 240 4 ’s ’s PART cana-2813 240 5 application application NOUN cana-2813 240 6 beyond beyond ADP cana-2813 240 7 cancer cancer NOUN cana-2813 240 8 to to ADP cana-2813 240 9 other other ADJ cana-2813 240 10 complex complex ADJ cana-2813 240 11 diseases disease NOUN cana-2813 240 12 , , PUNCT cana-2813 240 13 such such ADJ cana-2813 240 14 as as ADP cana-2813 240 15 neurodegenerative neurodegenerative ADJ cana-2813 240 16 disorders disorder NOUN cana-2813 240 17 or or CCONJ cana-2813 240 18 autoimmune autoimmune ADJ cana-2813 240 19 diseases disease NOUN cana-2813 240 20 , , PUNCT cana-2813 240 21 could could AUX cana-2813 240 22 also also ADV cana-2813 240 23 provide provide VERB cana-2813 240 24 valuable valuable ADJ cana-2813 240 25 insights insight NOUN cana-2813 240 26 into into ADP cana-2813 240 27 the the DET cana-2813 240 28 broader broad ADJ cana-2813 240 29 applicability applicability NOUN cana-2813 240 30 of of ADP cana-2813 240 31 this this DET cana-2813 240 32 approach approach NOUN cana-2813 240 33 . . PUNCT cana-2813 241 1 finally finally ADV cana-2813 241 2 , , PUNCT cana-2813 241 3 there there PRON cana-2813 241 4 is be VERB cana-2813 241 5 a a DET cana-2813 241 6 need need NOUN cana-2813 241 7 for for ADP cana-2813 241 8 extensive extensive ADJ cana-2813 241 9 validation validation NOUN cana-2813 241 10 of of ADP cana-2813 241 11 the the DET cana-2813 241 12 dnabert dnabert PROPN cana-2813 241 13 - - PUNCT cana-2813 241 14 mfo mfo NOUN cana-2813 241 15 model model NOUN cana-2813 241 16 in in ADP cana-2813 241 17 real real ADJ cana-2813 241 18 - - PUNCT cana-2813 241 19 world world NOUN cana-2813 241 20 clinical clinical ADJ cana-2813 241 21 settings setting NOUN cana-2813 241 22 . . PUNCT cana-2813 242 1 this this PRON cana-2813 242 2 includes include VERB cana-2813 242 3 testing test VERB cana-2813 242 4 the the DET cana-2813 242 5 model model NOUN cana-2813 242 6 on on ADP cana-2813 242 7 diverse diverse ADJ cana-2813 242 8 patient patient ADJ cana-2813 242 9 populations population NOUN cana-2813 242 10 , , PUNCT cana-2813 242 11 across across ADP cana-2813 242 12 different different ADJ cana-2813 242 13 healthcare healthcare NOUN cana-2813 242 14 systems system NOUN cana-2813 242 15 , , PUNCT cana-2813 242 16 and and CCONJ cana-2813 242 17 in in ADP cana-2813 242 18 various various ADJ cana-2813 242 19 clinical clinical ADJ cana-2813 242 20 contexts contexts NOUN cana-2813 242 21 . . PUNCT cana-2813 243 1 such such ADJ cana-2813 243 2 validation validation NOUN cana-2813 243 3 would would AUX cana-2813 243 4 help help VERB cana-2813 243 5 to to PART cana-2813 243 6 ensure ensure VERB cana-2813 243 7 that that SCONJ cana-2813 243 8 the the DET cana-2813 243 9 model model NOUN cana-2813 243 10 is be AUX cana-2813 243 11 robust robust ADJ cana-2813 243 12 , , PUNCT cana-2813 243 13 reliable reliable ADJ cana-2813 243 14 , , PUNCT cana-2813 243 15 and and CCONJ cana-2813 243 16 generalizable generalizable ADJ cana-2813 243 17 , , PUNCT cana-2813 243 18 paving pave VERB cana-2813 243 19 the the DET cana-2813 243 20 way way NOUN cana-2813 243 21 for for ADP cana-2813 243 22 its its PRON cana-2813 243 23 potential potential ADJ cana-2813 243 24 integration integration NOUN cana-2813 243 25 into into ADP cana-2813 243 26 clinical clinical ADJ cana-2813 243 27 workflows workflow NOUN cana-2813 243 28 . . PUNCT cana-2813 244 1 the the DET cana-2813 244 2 dnabert dnabert PROPN cana-2813 244 3 - - PUNCT cana-2813 244 4 mfo mfo NOUN cana-2813 244 5 framework framework NOUN cana-2813 244 6 was be AUX cana-2813 244 7 evaluated evaluate VERB cana-2813 244 8 on on ADP cana-2813 244 9 multiple multiple ADJ cana-2813 244 10 microarray microarray NOUN cana-2813 244 11 gene gene NOUN cana-2813 244 12 expression expression NOUN cana-2813 244 13 datasets dataset NOUN cana-2813 244 14 , , PUNCT cana-2813 244 15 including include VERB cana-2813 244 16 those those PRON cana-2813 244 17 from from ADP cana-2813 244 18 acute acute ADJ cana-2813 244 19 myeloid myeloid NOUN cana-2813 244 20 leukemia leukemia NOUN cana-2813 244 21 ( ( PUNCT cana-2813 244 22 aml aml PROPN cana-2813 244 23 ) ) PUNCT cana-2813 244 24 and and CCONJ cana-2813 244 25 acute acute ADJ cana-2813 244 26 lymphoblastic lymphoblastic ADJ cana-2813 244 27 leukemia leukemia NOUN cana-2813 244 28 ( ( PUNCT cana-2813 244 29 all all ADV cana-2813 244 30 ) ) PUNCT cana-2813 244 31 . . PUNCT cana-2813 245 1 the the DET cana-2813 245 2 results result NOUN cana-2813 245 3 demonstrated demonstrate VERB cana-2813 245 4 that that SCONJ cana-2813 245 5 dnabert dnabert NOUN cana-2813 245 6 - - PUNCT cana-2813 245 7 mfo mfo NOUN cana-2813 245 8 significantly significantly ADV cana-2813 245 9 improved improve VERB cana-2813 245 10 classification classification NOUN cana-2813 245 11 accuracy accuracy NOUN cana-2813 245 12 compared compare VERB cana-2813 245 13 to to ADP cana-2813 245 14 traditional traditional ADJ cana-2813 245 15 machine machine NOUN cana-2813 245 16 learning learning NOUN cana-2813 245 17 methods method NOUN cana-2813 245 18 and and CCONJ cana-2813 245 19 standalone standalone ADJ cana-2813 245 20 deep deep ADJ cana-2813 245 21 learning learning NOUN cana-2813 245 22 models model NOUN cana-2813 245 23 [ [ X cana-2813 245 24 29 29 NUM cana-2813 245 25 , , PUNCT cana-2813 245 26 30 30 NUM cana-2813 245 27 ] ] PUNCT cana-2813 245 28 . . PUNCT cana-2813 246 1 future future ADJ cana-2813 246 2 work work NOUN cana-2813 246 3 communications communication NOUN cana-2813 246 4 on on ADP cana-2813 246 5 applied apply VERB cana-2813 246 6 nonlinear nonlinear ADJ cana-2813 246 7 analysis analysis NOUN cana-2813 246 8 issn issn NOUN cana-2813 246 9 : : PUNCT cana-2813 246 10 1074 1074 NUM cana-2813 246 11 - - PUNCT cana-2813 246 12 133x 133x NUM cana-2813 246 13 vol vol NOUN cana-2813 246 14 32 32 NUM cana-2813 246 15 no no NOUN cana-2813 246 16 . . PUNCT cana-2813 247 1 4s 4s NUM cana-2813 247 2 ( ( PUNCT cana-2813 247 3 2025 2025 NUM cana-2813 247 4 ) ) PUNCT cana-2813 247 5 287 287 NUM cana-2813 247 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 247 7 will will AUX cana-2813 247 8 emphasis emphasis VERB cana-2813 247 9 on on ADP cana-2813 247 10 further far ADV cana-2813 247 11 optimizing optimize VERB cana-2813 247 12 the the DET cana-2813 247 13 framework framework NOUN cana-2813 247 14 and and CCONJ cana-2813 247 15 exploring explore VERB cana-2813 247 16 its its PRON cana-2813 247 17 applicability applicability NOUN cana-2813 247 18 to to ADP cana-2813 247 19 other other ADJ cana-2813 247 20 types type NOUN cana-2813 247 21 of of ADP cana-2813 247 22 genomic genomic ADJ cana-2813 247 23 data datum NOUN cana-2813 247 24 [ [ X cana-2813 247 25 31 31 NUM cana-2813 247 26 ] ] PUNCT cana-2813 247 27 . . PUNCT cana-2813 248 1 4 4 X cana-2813 248 2 . . X cana-2813 248 3 conclusion conclusion NOUN cana-2813 248 4 in in ADP cana-2813 248 5 summary summary NOUN cana-2813 248 6 , , PUNCT cana-2813 248 7 the the DET cana-2813 248 8 results result NOUN cana-2813 248 9 of of ADP cana-2813 248 10 this this DET cana-2813 248 11 study study NOUN cana-2813 248 12 showed show VERB cana-2813 248 13 that that SCONJ cana-2813 248 14 the the DET cana-2813 248 15 combination combination NOUN cana-2813 248 16 of of ADP cana-2813 248 17 transfer transfer NOUN cana-2813 248 18 learning learn VERB cana-2813 248 19 dnabert dnabert NOUN cana-2813 248 20 and and CCONJ cana-2813 248 21 mfo mfo PROPN cana-2813 248 22 provided provide VERB cana-2813 248 23 a a DET cana-2813 248 24 useful useful ADJ cana-2813 248 25 tool tool NOUN cana-2813 248 26 for for ADP cana-2813 248 27 the the DET cana-2813 248 28 classification classification NOUN cana-2813 248 29 of of ADP cana-2813 248 30 microarray microarray NOUN cana-2813 248 31 gene gene NOUN cana-2813 248 32 expression expression NOUN cana-2813 248 33 data datum NOUN cana-2813 248 34 . . PUNCT cana-2813 249 1 the the DET cana-2813 249 2 model model NOUN cana-2813 249 3 's 's PART cana-2813 249 4 high high ADJ cana-2813 249 5 accuracy accuracy NOUN cana-2813 249 6 , , PUNCT cana-2813 249 7 combined combine VERB cana-2813 249 8 with with ADP cana-2813 249 9 its its PRON cana-2813 249 10 ability ability NOUN cana-2813 249 11 to to PART cana-2813 249 12 generalize generalize VERB cana-2813 249 13 across across ADP cana-2813 249 14 different different ADJ cana-2813 249 15 cancer cancer NOUN cana-2813 249 16 types type NOUN cana-2813 249 17 and and CCONJ cana-2813 249 18 datasets dataset NOUN cana-2813 249 19 , , PUNCT cana-2813 249 20 suggests suggest VERB cana-2813 249 21 that that SCONJ cana-2813 249 22 this this DET cana-2813 249 23 approach approach NOUN cana-2813 249 24 could could AUX cana-2813 249 25 be be AUX cana-2813 249 26 highly highly ADV cana-2813 249 27 valuable valuable ADJ cana-2813 249 28 for for ADP cana-2813 249 29 clinical clinical ADJ cana-2813 249 30 applications application NOUN cana-2813 249 31 , , PUNCT cana-2813 249 32 particularly particularly ADV cana-2813 249 33 in in ADP cana-2813 249 34 the the DET cana-2813 249 35 early early ADJ cana-2813 249 36 diagnosis diagnosis NOUN cana-2813 249 37 and and CCONJ cana-2813 249 38 personalized personalized ADJ cana-2813 249 39 treatment treatment NOUN cana-2813 249 40 of of ADP cana-2813 249 41 cancer cancer NOUN cana-2813 249 42 . . PUNCT cana-2813 250 1 the the DET cana-2813 250 2 integration integration NOUN cana-2813 250 3 of of ADP cana-2813 250 4 dnabert dnabert NOUN cana-2813 250 5 and and CCONJ cana-2813 250 6 the the DET cana-2813 250 7 mayfly mayfly NOUN cana-2813 250 8 optimization optimization NOUN cana-2813 250 9 algorithm algorithm NOUN cana-2813 250 10 in in ADP cana-2813 250 11 the the DET cana-2813 250 12 classification classification NOUN cana-2813 250 13 of of ADP cana-2813 250 14 microarray microarray NOUN cana-2813 250 15 gene gene NOUN cana-2813 250 16 expression expression NOUN cana-2813 250 17 data datum NOUN cana-2813 250 18 represents represent VERB cana-2813 250 19 a a DET cana-2813 250 20 novel novel NOUN cana-2813 250 21 and and CCONJ cana-2813 250 22 promising promising ADJ cana-2813 250 23 approach approach NOUN cana-2813 250 24 to to ADP cana-2813 250 25 cancer cancer NOUN cana-2813 250 26 diagnosis diagnosis NOUN cana-2813 250 27 . . PUNCT cana-2813 251 1 while while SCONJ cana-2813 251 2 the the DET cana-2813 251 3 results result NOUN cana-2813 251 4 of of ADP cana-2813 251 5 this this DET cana-2813 251 6 study study NOUN cana-2813 251 7 are be AUX cana-2813 251 8 encouraging encouraging ADJ cana-2813 251 9 , , PUNCT cana-2813 251 10 critical critical ADJ cana-2813 251 11 challenges challenge NOUN cana-2813 251 12 remain remain VERB cana-2813 251 13 , , PUNCT cana-2813 251 14 particularly particularly ADV cana-2813 251 15 in in ADP cana-2813 251 16 terms term NOUN cana-2813 251 17 of of ADP cana-2813 251 18 generalizability generalizability NOUN cana-2813 251 19 , , PUNCT cana-2813 251 20 interpretability interpretability NOUN cana-2813 251 21 , , PUNCT cana-2813 251 22 and and CCONJ cana-2813 251 23 computational computational ADJ cana-2813 251 24 complexity complexity NOUN cana-2813 251 25 . . PUNCT cana-2813 252 1 addressing address VERB cana-2813 252 2 these these DET cana-2813 252 3 challenges challenge NOUN cana-2813 252 4 will will AUX cana-2813 252 5 require require VERB cana-2813 252 6 ongoing ongoing ADJ cana-2813 252 7 research research NOUN cana-2813 252 8 and and CCONJ cana-2813 252 9 collaboration collaboration NOUN cana-2813 252 10 between between ADP cana-2813 252 11 computational computational ADJ cana-2813 252 12 scientists scientist NOUN cana-2813 252 13 , , PUNCT cana-2813 252 14 clinicians clinician NOUN cana-2813 252 15 , , PUNCT cana-2813 252 16 and and CCONJ cana-2813 252 17 ethicists ethicist NOUN cana-2813 252 18 . . PUNCT cana-2813 253 1 ultimately ultimately ADV cana-2813 253 2 , , PUNCT cana-2813 253 3 the the DET cana-2813 253 4 successful successful ADJ cana-2813 253 5 application application NOUN cana-2813 253 6 of of ADP cana-2813 253 7 this this DET cana-2813 253 8 integrated integrate VERB cana-2813 253 9 model model NOUN cana-2813 253 10 could could AUX cana-2813 253 11 have have VERB cana-2813 253 12 a a DET cana-2813 253 13 transformative transformative ADJ cana-2813 253 14 impact impact NOUN cana-2813 253 15 on on ADP cana-2813 253 16 the the DET cana-2813 253 17 early early ADJ cana-2813 253 18 diagnosis diagnosis NOUN cana-2813 253 19 and and CCONJ cana-2813 253 20 personalized personalized ADJ cana-2813 253 21 treatment treatment NOUN cana-2813 253 22 of of ADP cana-2813 253 23 cancer cancer NOUN cana-2813 253 24 , , PUNCT cana-2813 253 25 contributing contribute VERB cana-2813 253 26 to to ADP cana-2813 253 27 improved improve VERB cana-2813 253 28 patient patient ADJ cana-2813 253 29 outcomes outcome NOUN cana-2813 253 30 and and CCONJ cana-2813 253 31 advancing advance VERB cana-2813 253 32 the the DET cana-2813 253 33 field field NOUN cana-2813 253 34 of of ADP cana-2813 253 35 precision precision NOUN cana-2813 253 36 medicine medicine NOUN cana-2813 253 37 . . PUNCT cana-2813 254 1 references reference NOUN cana-2813 254 2 [ [ X cana-2813 254 3 1 1 NUM cana-2813 254 4 ] ] PUNCT cana-2813 254 5 schena schena NOUN cana-2813 254 6 m m PROPN cana-2813 254 7 , , PUNCT cana-2813 254 8 shalon shalon PROPN cana-2813 254 9 d d PROPN cana-2813 254 10 , , PUNCT cana-2813 254 11 heller heller NOUN cana-2813 254 12 r r NOUN cana-2813 254 13 , , PUNCT cana-2813 254 14 chai chai NOUN cana-2813 254 15 a a DET cana-2813 254 16 , , PUNCT cana-2813 254 17 brown brown ADJ cana-2813 254 18 po po PROPN cana-2813 254 19 , , PUNCT cana-2813 254 20 davis davis PROPN cana-2813 254 21 rw rw PROPN cana-2813 254 22 . . PUNCT cana-2813 255 1 parallel parallel ADJ cana-2813 255 2 human human ADJ cana-2813 255 3 genome genome NOUN cana-2813 255 4 analysis analysis NOUN cana-2813 255 5 : : PUNCT cana-2813 255 6 microarray microarray NOUN cana-2813 255 7 - - PUNCT cana-2813 255 8 based base VERB cana-2813 255 9 expression expression NOUN cana-2813 255 10 monitoring monitoring NOUN cana-2813 255 11 of of ADP cana-2813 255 12 1000 1000 NUM cana-2813 255 13 genes gene NOUN cana-2813 255 14 . . PUNCT cana-2813 256 1 proc proc PROPN cana-2813 256 2 natl natl PROPN cana-2813 256 3 acad acad PROPN cana-2813 256 4 sci sci PROPN cana-2813 256 5 u u PROPN cana-2813 256 6 s s PROPN cana-2813 256 7 a. a. NOUN cana-2813 256 8 1996 1996 NUM cana-2813 256 9 oct oct NOUN cana-2813 256 10 1;93(20):10614 1;93(20):10614 NUM cana-2813 256 11 - - SYM cana-2813 256 12 9 9 NUM cana-2813 256 13 . . PUNCT cana-2813 256 14 doi doi NOUN cana-2813 256 15 : : PUNCT cana-2813 256 16 10.1073 10.1073 NUM cana-2813 256 17 / / SYM cana-2813 256 18 pnas.93.20.10614 pnas.93.20.10614 NOUN cana-2813 256 19 . . PUNCT cana-2813 257 1 pmid pmid NOUN cana-2813 257 2 : : PUNCT cana-2813 257 3 8855227 8855227 NUM cana-2813 257 4 [ [ X cana-2813 257 5 2 2 NUM cana-2813 257 6 ] ] SYM cana-2813 257 7 alon alon PROPN cana-2813 257 8 , , PUNCT cana-2813 257 9 u. u. PROPN cana-2813 257 10 , , PUNCT cana-2813 257 11 et et PROPN cana-2813 257 12 al al PROPN cana-2813 257 13 . . PROPN cana-2813 257 14 , , PUNCT cana-2813 257 15 " " PUNCT cana-2813 257 16 broad broad ADJ cana-2813 257 17 patterns pattern NOUN cana-2813 257 18 of of ADP cana-2813 257 19 gene gene NOUN cana-2813 257 20 expression expression NOUN cana-2813 257 21 revealed reveal VERB cana-2813 257 22 by by ADP cana-2813 257 23 clustering cluster VERB cana-2813 257 24 analysis analysis NOUN cana-2813 257 25 of of ADP cana-2813 257 26 tumor tumor NOUN cana-2813 257 27 samples sample NOUN cana-2813 257 28 , , PUNCT cana-2813 257 29 " " PUNCT cana-2813 257 30 journal journal NOUN cana-2813 257 31 of of ADP cana-2813 257 32 biological biological ADJ cana-2813 257 33 chemistry chemistry NOUN cana-2813 257 34 , , PUNCT cana-2813 257 35 vol vol NOUN cana-2813 257 36 . . PROPN cana-2813 257 37 273 273 NUM cana-2813 257 38 , , PUNCT cana-2813 257 39 no no INTJ cana-2813 257 40 . . NOUN cana-2813 257 41 27 27 NUM cana-2813 257 42 , , PUNCT cana-2813 257 43 pp pp ADJ cana-2813 257 44 . . PUNCT cana-2813 258 1 17974 17974 NUM cana-2813 258 2 - - SYM cana-2813 258 3 17981 17981 NUM cana-2813 258 4 , , PUNCT cana-2813 258 5 1998 1998 NUM cana-2813 258 6 . . PUNCT cana-2813 259 1 doi doi NOUN cana-2813 259 2 : : PUNCT cana-2813 259 3 http://doi.org/10.1074/jbc.273.27.17974 http://doi.org/10.1074/jbc.273.27.17974 PROPN cana-2813 260 1 [ [ X cana-2813 260 2 3 3 NUM cana-2813 260 3 ] ] X cana-2813 260 4 ding ding NOUN cana-2813 260 5 , , PUNCT cana-2813 260 6 c. c. NOUN cana-2813 260 7 , , PUNCT cana-2813 260 8 and and CCONJ cana-2813 260 9 simon simon PROPN cana-2813 260 10 , , PUNCT cana-2813 260 11 r. r. PROPN cana-2813 260 12 , , PUNCT cana-2813 260 13 " " PUNCT cana-2813 260 14 on on ADP cana-2813 260 15 the the DET cana-2813 260 16 choice choice NOUN cana-2813 260 17 of of ADP cana-2813 260 18 feature feature NOUN cana-2813 260 19 selection selection NOUN cana-2813 260 20 and and CCONJ cana-2813 260 21 classification classification NOUN cana-2813 260 22 methods method NOUN cana-2813 260 23 for for ADP cana-2813 260 24 microarray microarray NOUN cana-2813 260 25 data datum NOUN cana-2813 260 26 , , PUNCT cana-2813 260 27 " " PUNCT cana-2813 260 28 artificial artificial ADJ cana-2813 260 29 intelligence intelligence NOUN cana-2813 260 30 review review NOUN cana-2813 260 31 , , PUNCT cana-2813 260 32 vol vol NOUN cana-2813 260 33 . . PROPN cana-2813 260 34 15 15 NUM cana-2813 260 35 , , PUNCT cana-2813 260 36 no no INTJ cana-2813 260 37 . . NOUN cana-2813 260 38 1 1 NUM cana-2813 260 39 , , PUNCT cana-2813 260 40 pp pp ADJ cana-2813 260 41 . . PUNCT cana-2813 261 1 73 73 NUM cana-2813 261 2 - - SYM cana-2813 261 3 89 89 NUM cana-2813 261 4 , , PUNCT cana-2813 261 5 2001 2001 NUM cana-2813 261 6 . . PUNCT cana-2813 262 1 doi doi NOUN cana-2813 262 2 : : PUNCT cana-2813 262 3 http://doi.org/10.1023/a:1008945517840 http://doi.org/10.1023/a:1008945517840 NOUN cana-2813 263 1 [ [ X cana-2813 263 2 4 4 NUM cana-2813 263 3 ] ] X cana-2813 263 4 zhu zhu PROPN cana-2813 263 5 , , PUNCT cana-2813 263 6 j. j. PROPN cana-2813 263 7 , , PUNCT cana-2813 263 8 et et PROPN cana-2813 263 9 al al PROPN cana-2813 263 10 . . PROPN cana-2813 263 11 , , PUNCT cana-2813 263 12 " " PUNCT cana-2813 263 13 class class NOUN cana-2813 263 14 discovery discovery NOUN cana-2813 263 15 and and CCONJ cana-2813 263 16 classification classification NOUN cana-2813 263 17 with with ADP cana-2813 263 18 gene gene NOUN cana-2813 263 19 expression expression NOUN cana-2813 263 20 data datum NOUN cana-2813 263 21 , , PUNCT cana-2813 263 22 " " PUNCT cana-2813 263 23 biostatistics biostatistic NOUN cana-2813 263 24 , , PUNCT cana-2813 263 25 vol vol NOUN cana-2813 263 26 . . PROPN cana-2813 263 27 2 2 NUM cana-2813 263 28 , , PUNCT cana-2813 263 29 no no INTJ cana-2813 263 30 . . NOUN cana-2813 263 31 3 3 NUM cana-2813 263 32 , , PUNCT cana-2813 263 33 pp pp ADJ cana-2813 263 34 . . PUNCT cana-2813 263 35 365379 365379 NUM cana-2813 263 36 , , PUNCT cana-2813 263 37 2001 2001 NUM cana-2813 263 38 . . PUNCT cana-2813 264 1 doi doi NOUN cana-2813 264 2 : : PUNCT cana-2813 264 3 http://doi.org/10.1093/biostatistics/2.3.365 http://doi.org/10.1093/biostatistics/2.3.365 NOUN cana-2813 265 1 [ [ X cana-2813 265 2 5 5 NUM cana-2813 265 3 ] ] PUNCT cana-2813 265 4 beer beer NOUN cana-2813 265 5 , , PUNCT cana-2813 265 6 d. d. PROPN cana-2813 265 7 g. g. PROPN cana-2813 265 8 , , PUNCT cana-2813 265 9 et et PROPN cana-2813 265 10 al al PROPN cana-2813 265 11 . . PROPN cana-2813 265 12 , , PUNCT cana-2813 265 13 " " PUNCT cana-2813 265 14 gene gene NOUN cana-2813 265 15 - - PUNCT cana-2813 265 16 expression expression NOUN cana-2813 265 17 profiles profile NOUN cana-2813 265 18 predict predict VERB cana-2813 265 19 survival survival NOUN cana-2813 265 20 of of ADP cana-2813 265 21 patients patient NOUN cana-2813 265 22 with with ADP cana-2813 265 23 lung lung NOUN cana-2813 265 24 adenocarcinoma adenocarcinoma NOUN cana-2813 265 25 , , PUNCT cana-2813 265 26 " " PUNCT cana-2813 265 27 nature nature NOUN cana-2813 265 28 medicine medicine NOUN cana-2813 265 29 , , PUNCT cana-2813 265 30 vol vol NOUN cana-2813 265 31 . . PROPN cana-2813 265 32 8 8 NUM cana-2813 265 33 , , PUNCT cana-2813 265 34 no no INTJ cana-2813 265 35 . . NOUN cana-2813 265 36 8 8 NUM cana-2813 265 37 , , PUNCT cana-2813 265 38 pp pp ADJ cana-2813 265 39 . . PUNCT cana-2813 266 1 816 816 NUM cana-2813 266 2 - - SYM cana-2813 266 3 824 824 NUM cana-2813 266 4 , , PUNCT cana-2813 266 5 2002 2002 NUM cana-2813 266 6 . . PUNCT cana-2813 267 1 doi doi NOUN cana-2813 267 2 : : PUNCT cana-2813 268 1 http://doi.org/10.1038/nm733 http://doi.org/10.1038/nm733 PROPN cana-2813 268 2 [ [ X cana-2813 268 3 6 6 NUM cana-2813 268 4 ] ] PUNCT cana-2813 268 5 cortes corte NOUN cana-2813 268 6 , , PUNCT cana-2813 268 7 c. c. NOUN cana-2813 268 8 , , PUNCT cana-2813 268 9 and and CCONJ cana-2813 268 10 vapnik vapnik X cana-2813 268 11 , , PUNCT cana-2813 268 12 v. v. ADV cana-2813 268 13 , , PUNCT cana-2813 268 14 " " PUNCT cana-2813 268 15 support support NOUN cana-2813 268 16 - - PUNCT cana-2813 268 17 vector vector NOUN cana-2813 268 18 networks network NOUN cana-2813 268 19 , , PUNCT cana-2813 268 20 " " PUNCT cana-2813 268 21 machine machine NOUN cana-2813 268 22 learning learning NOUN cana-2813 268 23 , , PUNCT cana-2813 268 24 vol vol NOUN cana-2813 268 25 . . PROPN cana-2813 268 26 20 20 NUM cana-2813 268 27 , , PUNCT cana-2813 268 28 no no INTJ cana-2813 268 29 . . NOUN cana-2813 268 30 3 3 NUM cana-2813 268 31 , , PUNCT cana-2813 268 32 pp pp ADJ cana-2813 268 33 . . PUNCT cana-2813 269 1 273 273 NUM cana-2813 269 2 - - SYM cana-2813 269 3 297 297 NUM cana-2813 269 4 , , PUNCT cana-2813 269 5 1995 1995 NUM cana-2813 269 6 . . PUNCT cana-2813 270 1 doi doi NOUN cana-2813 270 2 : : PUNCT cana-2813 270 3 10.1007 10.1007 NUM cana-2813 270 4 / / SYM cana-2813 270 5 bf00994018 bf00994018 NOUN cana-2813 270 6 . . PUNCT cana-2813 271 1 [ [ X cana-2813 271 2 7 7 NUM cana-2813 271 3 ] ] PUNCT cana-2813 271 4 breiman breiman NOUN cana-2813 271 5 , , PUNCT cana-2813 271 6 l. l. PROPN cana-2813 271 7 , , PUNCT cana-2813 271 8 " " PUNCT cana-2813 271 9 random random ADJ cana-2813 271 10 forests forest NOUN cana-2813 271 11 , , PUNCT cana-2813 271 12 " " PUNCT cana-2813 271 13 machine machine NOUN cana-2813 271 14 learning learning NOUN cana-2813 271 15 , , PUNCT cana-2813 271 16 vol vol NOUN cana-2813 271 17 . . PROPN cana-2813 271 18 45 45 NUM cana-2813 271 19 , , PUNCT cana-2813 271 20 no no INTJ cana-2813 271 21 . . NOUN cana-2813 271 22 1 1 NUM cana-2813 271 23 , , PUNCT cana-2813 271 24 pp pp ADJ cana-2813 271 25 . . PUNCT cana-2813 271 26 5 5 NUM cana-2813 271 27 - - SYM cana-2813 271 28 32 32 NUM cana-2813 271 29 , , PUNCT cana-2813 271 30 2001 2001 NUM cana-2813 271 31 . . PUNCT cana-2813 271 32 , , PUNCT cana-2813 271 33 doi doi PROPN cana-2813 271 34 . . PUNCT cana-2813 272 1 https://doi.org/10.1023/a:1010933404324 https://doi.org/10.1023/a:1010933404324 ADJ cana-2813 272 2 [ [ X cana-2813 272 3 8 8 NUM cana-2813 272 4 ] ] PUNCT cana-2813 272 5 alter alter NOUN cana-2813 272 6 , , PUNCT cana-2813 272 7 o. o. PROPN cana-2813 272 8 , , PUNCT cana-2813 272 9 brown brown PROPN cana-2813 272 10 , , PUNCT cana-2813 272 11 p. p. PROPN cana-2813 272 12 o. o. PROPN cana-2813 272 13 , , PUNCT cana-2813 272 14 and and CCONJ cana-2813 272 15 botstein botstein ADJ cana-2813 272 16 , , PUNCT cana-2813 272 17 d. d. PROPN cana-2813 272 18 , , PUNCT cana-2813 272 19 " " PUNCT cana-2813 272 20 singular singular ADJ cana-2813 272 21 value value NOUN cana-2813 272 22 decomposition decomposition NOUN cana-2813 272 23 for for ADP cana-2813 272 24 microarray microarray NOUN cana-2813 272 25 data datum NOUN cana-2813 272 26 analysis analysis NOUN cana-2813 272 27 , , PUNCT cana-2813 272 28 " " PUNCT cana-2813 272 29 proceedings proceeding NOUN cana-2813 272 30 of of ADP cana-2813 272 31 the the DET cana-2813 272 32 national national PROPN cana-2813 272 33 academy academy PROPN cana-2813 272 34 of of ADP cana-2813 272 35 sciences sciences PROPN cana-2813 272 36 , , PUNCT cana-2813 272 37 vol vol NOUN cana-2813 272 38 . . PROPN cana-2813 273 1 97 97 NUM cana-2813 273 2 , , PUNCT cana-2813 273 3 no no INTJ cana-2813 273 4 . . NOUN cana-2813 273 5 18 18 NUM cana-2813 273 6 , , PUNCT cana-2813 273 7 pp pp ADJ cana-2813 273 8 . . PUNCT cana-2813 274 1 10101 10101 NUM cana-2813 274 2 - - SYM cana-2813 274 3 10106 10106 NUM cana-2813 274 4 , , PUNCT cana-2813 274 5 2000 2000 NUM cana-2813 274 6 . . PUNCT cana-2813 275 1 doi doi NOUN cana-2813 275 2 : : PUNCT cana-2813 275 3 http://doi.org/10.1073/pnas.97.18.10101 http://doi.org/10.1073/pnas.97.18.10101 PROPN cana-2813 275 4 [ [ X cana-2813 275 5 9 9 NUM cana-2813 275 6 ] ] PUNCT cana-2813 275 7 cover cover NOUN cana-2813 275 8 , , PUNCT cana-2813 275 9 t. t. NOUN cana-2813 275 10 , , PUNCT cana-2813 275 11 and and CCONJ cana-2813 275 12 hart hart PROPN cana-2813 275 13 , , PUNCT cana-2813 275 14 p. p. PROPN cana-2813 275 15 , , PUNCT cana-2813 275 16 " " PUNCT cana-2813 275 17 nearest near ADJ cana-2813 275 18 neighbor neighbor NOUN cana-2813 275 19 pattern pattern NOUN cana-2813 275 20 classification classification NOUN cana-2813 275 21 , , PUNCT cana-2813 275 22 " " PUNCT cana-2813 275 23 ieee ieee NOUN cana-2813 275 24 transactions transaction NOUN cana-2813 275 25 on on ADP cana-2813 275 26 information information NOUN cana-2813 275 27 theory theory NOUN cana-2813 275 28 , , PUNCT cana-2813 275 29 vol vol NOUN cana-2813 275 30 . . PROPN cana-2813 275 31 13 13 NUM cana-2813 275 32 , , PUNCT cana-2813 275 33 no no INTJ cana-2813 275 34 . . NOUN cana-2813 275 35 1 1 NUM cana-2813 275 36 , , PUNCT cana-2813 275 37 pp pp ADJ cana-2813 275 38 . . PUNCT cana-2813 276 1 21 21 NUM cana-2813 276 2 - - SYM cana-2813 276 3 27 27 NUM cana-2813 276 4 , , PUNCT cana-2813 276 5 1967 1967 NUM cana-2813 276 6 . . PUNCT cana-2813 277 1 doi doi NOUN cana-2813 277 2 : : PUNCT cana-2813 277 3 http://doi.org/10.1109/tit.1967.1053964 http://doi.org/10.1109/tit.1967.1053964 PROPN cana-2813 278 1 [ [ X cana-2813 278 2 10 10 NUM cana-2813 278 3 ] ] X cana-2813 278 4 breiman breiman NOUN cana-2813 278 5 , , PUNCT cana-2813 278 6 l. l. PROPN cana-2813 278 7 , , PUNCT cana-2813 278 8 " " PUNCT cana-2813 278 9 bagging bagging NOUN cana-2813 278 10 predictors predictor NOUN cana-2813 278 11 , , PUNCT cana-2813 278 12 " " PUNCT cana-2813 278 13 machine machine NOUN cana-2813 278 14 learning learning NOUN cana-2813 278 15 , , PUNCT cana-2813 278 16 vol vol NOUN cana-2813 278 17 . . PROPN cana-2813 278 18 24 24 NUM cana-2813 278 19 , , PUNCT cana-2813 278 20 no no INTJ cana-2813 278 21 . . NOUN cana-2813 278 22 2 2 NUM cana-2813 278 23 , , PUNCT cana-2813 278 24 pp pp ADJ cana-2813 278 25 . . PUNCT cana-2813 279 1 123 123 NUM cana-2813 279 2 - - SYM cana-2813 279 3 140 140 NUM cana-2813 279 4 , , PUNCT cana-2813 279 5 1996 1996 NUM cana-2813 279 6 . . PUNCT cana-2813 280 1 doi doi NOUN cana-2813 280 2 : : PUNCT cana-2813 280 3 http://doi.org/10.1023/a:1018054314350 http://doi.org/10.1023/a:1018054314350 PROPN cana-2813 281 1 [ [ X cana-2813 281 2 11 11 NUM cana-2813 281 3 ] ] X cana-2813 281 4 liaw liaw PROPN cana-2813 281 5 , , PUNCT cana-2813 281 6 a. a. NOUN cana-2813 281 7 , , PUNCT cana-2813 281 8 and and CCONJ cana-2813 281 9 wiener wiener NOUN cana-2813 281 10 , , PUNCT cana-2813 281 11 m. m. NOUN cana-2813 281 12 , , PUNCT cana-2813 281 13 " " PUNCT cana-2813 281 14 classification classification NOUN cana-2813 281 15 and and CCONJ cana-2813 281 16 regression regression NOUN cana-2813 281 17 by by ADP cana-2813 281 18 randomforest randomfor ADJ cana-2813 281 19 , , PUNCT cana-2813 281 20 " " PUNCT cana-2813 281 21 r r NOUN cana-2813 281 22 news news NOUN cana-2813 281 23 , , PUNCT cana-2813 281 24 vol vol NOUN cana-2813 281 25 . . PROPN cana-2813 281 26 2 2 NUM cana-2813 281 27 , , PUNCT cana-2813 281 28 no no INTJ cana-2813 281 29 . . NOUN cana-2813 281 30 3 3 NUM cana-2813 281 31 , , PUNCT cana-2813 281 32 pp pp ADJ cana-2813 281 33 . . PUNCT cana-2813 281 34 18 18 NUM cana-2813 281 35 - - SYM cana-2813 281 36 22 22 NUM cana-2813 281 37 , , PUNCT cana-2813 281 38 2002 2002 NUM cana-2813 281 39 . . PUNCT cana-2813 282 1 [ [ X cana-2813 282 2 12 12 NUM cana-2813 282 3 ] ] X cana-2813 282 4 lecun lecun ADJ cana-2813 282 5 , , PUNCT cana-2813 282 6 y. y. PROPN cana-2813 282 7 , , PUNCT cana-2813 282 8 et et PROPN cana-2813 282 9 al al PROPN cana-2813 282 10 . . PROPN cana-2813 282 11 , , PUNCT cana-2813 282 12 " " PUNCT cana-2813 282 13 gradient gradient NOUN cana-2813 282 14 - - PUNCT cana-2813 282 15 based base VERB cana-2813 282 16 learning learning NOUN cana-2813 282 17 applied apply VERB cana-2813 282 18 to to ADP cana-2813 282 19 document document NOUN cana-2813 282 20 recognition recognition NOUN cana-2813 282 21 , , PUNCT cana-2813 282 22 " " PUNCT cana-2813 282 23 proceedings proceeding NOUN cana-2813 282 24 of of ADP cana-2813 282 25 the the DET cana-2813 282 26 ieee ieee NOUN cana-2813 282 27 , , PUNCT cana-2813 282 28 vol vol NOUN cana-2813 282 29 . . PROPN cana-2813 282 30 86 86 NUM cana-2813 282 31 , , PUNCT cana-2813 282 32 no no INTJ cana-2813 282 33 . . NOUN cana-2813 282 34 11 11 NUM cana-2813 282 35 , , PUNCT cana-2813 282 36 pp pp ADJ cana-2813 282 37 . . PUNCT cana-2813 282 38 2278 2278 NUM cana-2813 282 39 - - SYM cana-2813 282 40 2324 2324 NUM cana-2813 282 41 , , PUNCT cana-2813 282 42 1998 1998 NUM cana-2813 282 43 . . PUNCT cana-2813 283 1 doi doi NOUN cana-2813 283 2 : : PUNCT cana-2813 283 3 http://doi.org/10.1109/5.726791 http://doi.org/10.1109/5.726791 SYM cana-2813 283 4 http://doi.org/10.1074/jbc.273.27.17974 http://doi.org/10.1074/jbc.273.27.17974 NOUN cana-2813 283 5 http://doi.org/10.1074/jbc.273.27.17974 http://doi.org/10.1074/jbc.273.27.17974 PROPN cana-2813 283 6 http://doi.org/10.1023/a:1008945517840 http://doi.org/10.1023/a:1008945517840 NOUN cana-2813 283 7 http://doi.org/10.1093/biostatistics/2.3.365 http://doi.org/10.1093/biostatistics/2.3.365 VERB cana-2813 283 8 http://doi.org/10.1038/nm733 http://doi.org/10.1038/nm733 PROPN cana-2813 283 9 https://doi.org/10.1023/a:1010933404324 https://doi.org/10.1023/a:1010933404324 ADP cana-2813 283 10 http://doi.org/10.1073/pnas.97.18.10101 http://doi.org/10.1073/pnas.97.18.10101 PROPN cana-2813 283 11 http://doi.org/10.1109/tit.1967.1053964 http://doi.org/10.1109/tit.1967.1053964 VERB cana-2813 283 12 http://doi.org/10.1023/a:1018054314350 http://doi.org/10.1023/a:1018054314350 PROPN cana-2813 283 13 http://doi.org/10.1109/5.726791 http://doi.org/10.1109/5.726791 NOUN cana-2813 283 14 communications communication NOUN cana-2813 283 15 on on ADP cana-2813 283 16 applied apply VERB cana-2813 283 17 nonlinear nonlinear ADJ cana-2813 283 18 analysis analysis NOUN cana-2813 283 19 issn issn NOUN cana-2813 283 20 : : PUNCT cana-2813 283 21 1074 1074 NUM cana-2813 283 22 - - PUNCT cana-2813 283 23 133x 133x NUM cana-2813 283 24 vol vol NOUN cana-2813 283 25 32 32 NUM cana-2813 283 26 no no NOUN cana-2813 283 27 . . PUNCT cana-2813 284 1 4s 4s NUM cana-2813 284 2 ( ( PUNCT cana-2813 284 3 2025 2025 NUM cana-2813 284 4 ) ) PUNCT cana-2813 284 5 288 288 NUM cana-2813 284 6 https://internationalpubls.com https://internationalpubls.com X cana-2813 285 1 [ [ X cana-2813 285 2 13 13 NUM cana-2813 285 3 ] ] X cana-2813 285 4 hochreiter hochreiter PROPN cana-2813 285 5 , , PUNCT cana-2813 285 6 s. s. PROPN cana-2813 285 7 , , PUNCT cana-2813 285 8 and and CCONJ cana-2813 285 9 schmidhuber schmidhuber NOUN cana-2813 285 10 , , PUNCT cana-2813 285 11 j. j. PROPN cana-2813 285 12 , , PUNCT cana-2813 285 13 " " PUNCT cana-2813 285 14 long long ADJ cana-2813 285 15 short short ADJ cana-2813 285 16 - - PUNCT cana-2813 285 17 term term NOUN cana-2813 285 18 memory memory NOUN cana-2813 285 19 , , PUNCT cana-2813 285 20 " " PUNCT cana-2813 285 21 neural neural ADJ cana-2813 285 22 computation computation NOUN cana-2813 285 23 , , PUNCT cana-2813 285 24 vol vol NOUN cana-2813 285 25 . . PROPN cana-2813 286 1 9 9 NUM cana-2813 286 2 , , PUNCT cana-2813 286 3 no no INTJ cana-2813 286 4 . . NOUN cana-2813 286 5 8 8 NUM cana-2813 286 6 , , PUNCT cana-2813 286 7 pp pp ADJ cana-2813 286 8 . . PUNCT cana-2813 287 1 17351780 17351780 NUM cana-2813 287 2 , , PUNCT cana-2813 287 3 1997 1997 NUM cana-2813 287 4 . . PUNCT cana-2813 288 1 doi doi NOUN cana-2813 288 2 : : PUNCT cana-2813 288 3 http://doi.org/10.1162/neco.1997.9.8.1735 http://doi.org/10.1162/neco.1997.9.8.1735 PROPN cana-2813 289 1 [ [ X cana-2813 289 2 14 14 NUM cana-2813 289 3 ] ] X cana-2813 289 4 liu liu PROPN cana-2813 289 5 , , PUNCT cana-2813 289 6 y. y. PROPN cana-2813 289 7 , , PUNCT cana-2813 289 8 and and CCONJ cana-2813 289 9 hoi hoi PROPN cana-2813 289 10 , , PUNCT cana-2813 289 11 s.c.h s.c.h ADJ cana-2813 289 12 . . PROPN cana-2813 289 13 , , PUNCT cana-2813 289 14 " " PUNCT cana-2813 289 15 deep deep ADJ cana-2813 289 16 learning learning NOUN cana-2813 289 17 for for ADP cana-2813 289 18 genomics genomics NOUN cana-2813 289 19 , , PUNCT cana-2813 289 20 " " PUNCT cana-2813 289 21 journal journal NOUN cana-2813 289 22 of of ADP cana-2813 289 23 computational computational ADJ cana-2813 289 24 biology biology NOUN cana-2813 289 25 , , PUNCT cana-2813 289 26 vol vol NOUN cana-2813 289 27 . . PROPN cana-2813 289 28 23 23 NUM cana-2813 289 29 , , PUNCT cana-2813 289 30 no no INTJ cana-2813 289 31 . . NOUN cana-2813 289 32 5 5 NUM cana-2813 289 33 , , PUNCT cana-2813 289 34 pp pp ADJ cana-2813 289 35 . . PUNCT cana-2813 289 36 340351 340351 NUM cana-2813 289 37 , , PUNCT cana-2813 289 38 2016 2016 NUM cana-2813 289 39 . . PUNCT cana-2813 290 1 doi doi NOUN cana-2813 290 2 : : PUNCT cana-2813 290 3 http://doi.org/10.1089/cmb.2015.0232 http://doi.org/10.1089/cmb.2015.0232 PROPN cana-2813 291 1 [ [ X cana-2813 291 2 15 15 NUM cana-2813 291 3 ] ] X cana-2813 291 4 yosinski yosinski ADJ cana-2813 291 5 , , PUNCT cana-2813 291 6 j. j. PROPN cana-2813 291 7 , , PUNCT cana-2813 291 8 et et PROPN cana-2813 291 9 al al PROPN cana-2813 291 10 . . PROPN cana-2813 291 11 , , PUNCT cana-2813 291 12 " " PUNCT cana-2813 291 13 how how SCONJ cana-2813 291 14 transferable transferable ADJ cana-2813 291 15 are be AUX cana-2813 291 16 features feature NOUN cana-2813 291 17 in in ADP cana-2813 291 18 deep deep ADJ cana-2813 291 19 neural neural ADJ cana-2813 291 20 networks network NOUN cana-2813 291 21 ? ? PUNCT cana-2813 291 22 " " PUNCT cana-2813 291 23 advances advance NOUN cana-2813 291 24 in in ADP cana-2813 291 25 neural neural ADJ cana-2813 291 26 information information NOUN cana-2813 291 27 processing processing NOUN cana-2813 291 28 systems system NOUN cana-2813 291 29 , , PUNCT cana-2813 291 30 vol vol NOUN cana-2813 291 31 . . PROPN cana-2813 291 32 27 27 NUM cana-2813 291 33 , , PUNCT cana-2813 291 34 2014 2014 NUM cana-2813 291 35 . . PUNCT cana-2813 292 1 [ [ X cana-2813 292 2 16 16 NUM cana-2813 292 3 ] ] X cana-2813 292 4 liu liu PROPN cana-2813 292 5 , , PUNCT cana-2813 292 6 l. l. PROPN cana-2813 292 7 , , PUNCT cana-2813 292 8 et et PROPN cana-2813 292 9 al al PROPN cana-2813 292 10 . . PROPN cana-2813 292 11 , , PUNCT cana-2813 292 12 " " PUNCT cana-2813 292 13 dnabert dnabert NOUN cana-2813 292 14 : : PUNCT cana-2813 292 15 pre pre ADJ cana-2813 292 16 - - ADJ cana-2813 292 17 trained train VERB cana-2813 292 18 bidirectional bidirectional ADJ cana-2813 292 19 encoder encoder NOUN cana-2813 292 20 representations representation VERB cana-2813 292 21 from from ADP cana-2813 292 22 transformers transformer NOUN cana-2813 292 23 model model NOUN cana-2813 292 24 for for ADP cana-2813 292 25 dnalanguage dnalanguage NOUN cana-2813 292 26 in in ADP cana-2813 292 27 genome genome NOUN cana-2813 292 28 , , PUNCT cana-2813 292 29 " " PUNCT cana-2813 292 30 bioinformatics bioinformatics NOUN cana-2813 292 31 , , PUNCT cana-2813 292 32 vol vol NOUN cana-2813 292 33 . . PROPN cana-2813 293 1 36 36 NUM cana-2813 293 2 , , PUNCT cana-2813 293 3 no no INTJ cana-2813 293 4 . . NOUN cana-2813 293 5 20 20 NUM cana-2813 293 6 , , PUNCT cana-2813 293 7 pp pp ADJ cana-2813 293 8 . . PUNCT cana-2813 294 1 4983 4983 NUM cana-2813 294 2 - - SYM cana-2813 294 3 4990 4990 NUM cana-2813 294 4 , , PUNCT cana-2813 294 5 2020 2020 NUM cana-2813 294 6 . . PUNCT cana-2813 295 1 doi doi NOUN cana-2813 295 2 : : PUNCT cana-2813 295 3 http://doi.org/10.1093/bioinformatics/btaa741 http://doi.org/10.1093/bioinformatics/btaa741 VERB cana-2813 296 1 [ [ X cana-2813 296 2 17 17 NUM cana-2813 296 3 ] ] X cana-2813 296 4 zhang zhang PROPN cana-2813 296 5 , , PUNCT cana-2813 296 6 l. l. PROPN cana-2813 296 7 , , PUNCT cana-2813 296 8 et et PROPN cana-2813 296 9 al al PROPN cana-2813 296 10 . . PROPN cana-2813 296 11 , , PUNCT cana-2813 296 12 " " PUNCT cana-2813 296 13 a a DET cana-2813 296 14 novel novel ADJ cana-2813 296 15 mayfly mayfly NOUN cana-2813 296 16 optimization optimization NOUN cana-2813 296 17 algorithm algorithm NOUN cana-2813 296 18 for for ADP cana-2813 296 19 solving solve VERB cana-2813 296 20 optimization optimization NOUN cana-2813 296 21 problems problem NOUN cana-2813 296 22 , , PUNCT cana-2813 296 23 " " PUNCT cana-2813 296 24 soft soft ADJ cana-2813 296 25 computing computing NOUN cana-2813 296 26 , , PUNCT cana-2813 296 27 vol vol NOUN cana-2813 296 28 . . PROPN cana-2813 296 29 21 21 NUM cana-2813 296 30 , , PUNCT cana-2813 296 31 no no INTJ cana-2813 296 32 . . NOUN cana-2813 296 33 4 4 NUM cana-2813 296 34 , , PUNCT cana-2813 296 35 pp pp ADJ cana-2813 296 36 . . PUNCT cana-2813 297 1 1035 1035 NUM cana-2813 297 2 - - SYM cana-2813 297 3 1047 1047 NUM cana-2813 297 4 , , PUNCT cana-2813 297 5 2017 2017 NUM cana-2813 297 6 . . PUNCT cana-2813 298 1 doi doi NOUN cana-2813 298 2 : : PUNCT cana-2813 298 3 http://doi.org/10.1007/s00500-015-1865-0 http://doi.org/10.1007/s00500-015-1865-0 NUM cana-2813 299 1 [ [ X cana-2813 299 2 18 18 NUM cana-2813 299 3 ] ] X cana-2813 299 4 goldberg goldberg PROPN cana-2813 299 5 , , PUNCT cana-2813 299 6 d.e d.e PROPN cana-2813 299 7 . . PROPN cana-2813 299 8 , , PUNCT cana-2813 299 9 " " PUNCT cana-2813 299 10 genetic genetic ADJ cana-2813 299 11 algorithms algorithm NOUN cana-2813 299 12 in in ADP cana-2813 299 13 search search NOUN cana-2813 299 14 , , PUNCT cana-2813 299 15 optimization optimization NOUN cana-2813 299 16 , , PUNCT cana-2813 299 17 and and CCONJ cana-2813 299 18 machine machine NOUN cana-2813 299 19 learning learning NOUN cana-2813 299 20 , , PUNCT cana-2813 299 21 " " PUNCT cana-2813 299 22 addison addison PROPN cana-2813 299 23 - - PUNCT cana-2813 299 24 wesley wesley PROPN cana-2813 299 25 , , PUNCT cana-2813 299 26 1989 1989 NUM cana-2813 299 27 . . PUNCT cana-2813 300 1 [ [ X cana-2813 300 2 19 19 NUM cana-2813 300 3 ] ] X cana-2813 300 4 kennedy kennedy PROPN cana-2813 300 5 , , PUNCT cana-2813 300 6 j. j. PROPN cana-2813 300 7 , , PUNCT cana-2813 300 8 and and CCONJ cana-2813 300 9 eberhart eberhart NOUN cana-2813 300 10 , , PUNCT cana-2813 300 11 r. r. PROPN cana-2813 300 12 , , PUNCT cana-2813 300 13 " " PUNCT cana-2813 300 14 particle particle NOUN cana-2813 300 15 swarm swarm NOUN cana-2813 300 16 optimization optimization NOUN cana-2813 300 17 , , PUNCT cana-2813 300 18 " " PUNCT cana-2813 300 19 proceedings proceeding NOUN cana-2813 300 20 of of ADP cana-2813 300 21 the the DET cana-2813 300 22 ieee ieee NOUN cana-2813 300 23 international international PROPN cana-2813 300 24 conference conference NOUN cana-2813 300 25 on on ADP cana-2813 300 26 neural neural ADJ cana-2813 300 27 networks network NOUN cana-2813 300 28 , , PUNCT cana-2813 300 29 vol vol NOUN cana-2813 300 30 . . PROPN cana-2813 300 31 4 4 NUM cana-2813 300 32 , , PUNCT cana-2813 300 33 pp pp ADJ cana-2813 300 34 . . PUNCT cana-2813 300 35 1942 1942 NUM cana-2813 300 36 - - SYM cana-2813 300 37 1948 1948 NUM cana-2813 300 38 , , PUNCT cana-2813 300 39 1995 1995 NUM cana-2813 300 40 . . PUNCT cana-2813 301 1 doi doi NOUN cana-2813 301 2 : : PUNCT cana-2813 301 3 http://doi.org/10.1109/icnn.1995.488968 http://doi.org/10.1109/icnn.1995.488968 NOUN cana-2813 302 1 [ [ X cana-2813 302 2 20 20 NUM cana-2813 302 3 ] ] X cana-2813 302 4 dorigo dorigo PROPN cana-2813 302 5 , , PUNCT cana-2813 302 6 m. m. NOUN cana-2813 302 7 , , PUNCT cana-2813 302 8 and and CCONJ cana-2813 302 9 stΓΌtzle stΓΌtzle NOUN cana-2813 302 10 , , PUNCT cana-2813 302 11 t. t. NOUN cana-2813 302 12 , , PUNCT cana-2813 302 13 " " PUNCT cana-2813 302 14 ant ant ADJ cana-2813 302 15 colony colony NOUN cana-2813 302 16 optimization optimization NOUN cana-2813 302 17 , , PUNCT cana-2813 302 18 " " PUNCT cana-2813 302 19 mit mit PROPN cana-2813 302 20 press press NOUN cana-2813 302 21 , , PUNCT cana-2813 302 22 2004 2004 NUM cana-2813 302 23 . . PUNCT cana-2813 303 1 [ [ X cana-2813 303 2 21 21 NUM cana-2813 303 3 ] ] X cana-2813 303 4 mirjalili mirjalili NOUN cana-2813 303 5 , , PUNCT cana-2813 303 6 s. s. PROPN cana-2813 303 7 , , PUNCT cana-2813 303 8 and and CCONJ cana-2813 303 9 lewis lewis PROPN cana-2813 303 10 , , PUNCT cana-2813 303 11 a. a. NOUN cana-2813 303 12 , , PUNCT cana-2813 303 13 " " PUNCT cana-2813 303 14 the the DET cana-2813 303 15 influence influence NOUN cana-2813 303 16 of of ADP cana-2813 303 17 mutation mutation NOUN cana-2813 303 18 operators operator NOUN cana-2813 303 19 on on ADP cana-2813 303 20 the the DET cana-2813 303 21 performance performance NOUN cana-2813 303 22 of of ADP cana-2813 303 23 genetic genetic ADJ cana-2813 303 24 algorithms algorithm NOUN cana-2813 303 25 , , PUNCT cana-2813 303 26 " " PUNCT cana-2813 303 27 evolutionary evolutionary ADJ cana-2813 303 28 computation computation NOUN cana-2813 303 29 , , PUNCT cana-2813 303 30 vol vol NOUN cana-2813 303 31 . . PROPN cana-2813 303 32 18 18 NUM cana-2813 303 33 , , PUNCT cana-2813 303 34 no no INTJ cana-2813 303 35 . . NOUN cana-2813 303 36 3 3 NUM cana-2813 303 37 , , PUNCT cana-2813 303 38 pp pp ADJ cana-2813 303 39 . . PUNCT cana-2813 304 1 377 377 NUM cana-2813 304 2 - - SYM cana-2813 304 3 393 393 NUM cana-2813 304 4 , , PUNCT cana-2813 304 5 2010 2010 NUM cana-2813 304 6 . . PUNCT cana-2813 305 1 doi doi NOUN cana-2813 305 2 : : PUNCT cana-2813 305 3 http://doi.org/10.1162/evco_a_00009 http://doi.org/10.1162/evco_a_00009 X cana-2813 306 1 [ [ X cana-2813 306 2 22 22 NUM cana-2813 306 3 ] ] X cana-2813 306 4 wang wang PROPN cana-2813 306 5 , , PUNCT cana-2813 306 6 j. j. PROPN cana-2813 306 7 , , PUNCT cana-2813 306 8 et et PROPN cana-2813 306 9 al al PROPN cana-2813 306 10 . . PROPN cana-2813 306 11 , , PUNCT cana-2813 306 12 " " PUNCT cana-2813 306 13 markov markov NOUN cana-2813 306 14 blanket blanket NOUN cana-2813 306 15 - - PUNCT cana-2813 306 16 embedded embed VERB cana-2813 306 17 genetic genetic ADJ cana-2813 306 18 algorithm algorithm NOUN cana-2813 306 19 for for ADP cana-2813 306 20 gene gene NOUN cana-2813 306 21 selection selection NOUN cana-2813 306 22 , , PUNCT cana-2813 306 23 " " PUNCT cana-2813 306 24 ieee ieee NOUN cana-2813 306 25 transactions transaction NOUN cana-2813 306 26 on on ADP cana-2813 306 27 biomedical biomedical ADJ cana-2813 306 28 engineering engineering NOUN cana-2813 306 29 , , PUNCT cana-2813 306 30 vol vol NOUN cana-2813 306 31 . . PROPN cana-2813 306 32 63 63 NUM cana-2813 306 33 , , PUNCT cana-2813 306 34 no no INTJ cana-2813 306 35 . . NOUN cana-2813 306 36 8 8 NUM cana-2813 306 37 , , PUNCT cana-2813 306 38 pp pp ADJ cana-2813 306 39 . . PUNCT cana-2813 306 40 1742 1742 NUM cana-2813 306 41 - - SYM cana-2813 306 42 1752 1752 NUM cana-2813 306 43 , , PUNCT cana-2813 306 44 2016 2016 NUM cana-2813 306 45 . . PUNCT cana-2813 307 1 doi doi NOUN cana-2813 307 2 : : PUNCT cana-2813 308 1 http://doi.org/10.1109/tbme.2015.2500184 http://doi.org/10.1109/tbme.2015.2500184 PROPN cana-2813 308 2 [ [ X cana-2813 308 3 23 23 NUM cana-2813 308 4 ] ] X cana-2813 308 5 devlin devlin PROPN cana-2813 308 6 , , PUNCT cana-2813 308 7 j. j. PROPN cana-2813 308 8 , , PUNCT cana-2813 308 9 et et PROPN cana-2813 308 10 al al PROPN cana-2813 308 11 . . PROPN cana-2813 308 12 , , PUNCT cana-2813 308 13 " " PUNCT cana-2813 308 14 bert bert NOUN cana-2813 308 15 : : PUNCT cana-2813 308 16 pre pre ADJ cana-2813 308 17 - - NOUN cana-2813 308 18 training training NOUN cana-2813 308 19 of of ADP cana-2813 308 20 deep deep ADJ cana-2813 308 21 bidirectional bidirectional ADJ cana-2813 308 22 transformers transformer NOUN cana-2813 308 23 for for ADP cana-2813 308 24 language language NOUN cana-2813 308 25 understanding understanding NOUN cana-2813 308 26 , , PUNCT cana-2813 308 27 " " PUNCT cana-2813 308 28 arxiv arxiv PROPN cana-2813 308 29 preprint preprint NOUN cana-2813 308 30 , , PUNCT cana-2813 308 31 2018 2018 NUM cana-2813 308 32 . . PUNCT cana-2813 309 1 arxiv:1810.04805 arxiv:1810.04805 PROPN cana-2813 309 2 . . PUNCT cana-2813 310 1 [ [ X cana-2813 310 2 24 24 NUM cana-2813 310 3 ] ] SYM cana-2813 310 4 vaswani vaswani NOUN cana-2813 310 5 , , PUNCT cana-2813 310 6 a. a. NOUN cana-2813 310 7 , , PUNCT cana-2813 310 8 et et PROPN cana-2813 310 9 al al PROPN cana-2813 310 10 . . PROPN cana-2813 310 11 , , PUNCT cana-2813 310 12 " " PUNCT cana-2813 310 13 attention attention NOUN cana-2813 310 14 is be AUX cana-2813 310 15 all all PRON cana-2813 310 16 you you PRON cana-2813 310 17 need need VERB cana-2813 310 18 , , PUNCT cana-2813 310 19 " " PUNCT cana-2813 310 20 advances advance NOUN cana-2813 310 21 in in ADP cana-2813 310 22 neural neural ADJ cana-2813 310 23 information information NOUN cana-2813 310 24 processing processing NOUN cana-2813 310 25 systems system NOUN cana-2813 310 26 , , PUNCT cana-2813 310 27 vol vol NOUN cana-2813 310 28 . . PROPN cana-2813 310 29 30 30 NUM cana-2813 310 30 , , PUNCT cana-2813 310 31 2017 2017 NUM cana-2813 310 32 . . PUNCT cana-2813 311 1 doi doi NOUN cana-2813 311 2 : : PUNCT cana-2813 311 3 http://doi.org/10.48550/arxiv.1706.03762 http://doi.org/10.48550/arxiv.1706.03762 PROPN cana-2813 312 1 [ [ X cana-2813 312 2 25 25 NUM cana-2813 312 3 ] ] PUNCT cana-2813 312 4 mirjalili mirjalili NOUN cana-2813 312 5 , , PUNCT cana-2813 312 6 s. s. PROPN cana-2813 312 7 , , PUNCT cana-2813 312 8 and and CCONJ cana-2813 312 9 fattahzadeh fattahzadeh PROPN cana-2813 312 10 , , PUNCT cana-2813 312 11 m. m. NOUN cana-2813 312 12 , , PUNCT cana-2813 312 13 " " PUNCT cana-2813 312 14 mayfly mayfly NOUN cana-2813 312 15 optimization optimization NOUN cana-2813 312 16 algorithm algorithm NOUN cana-2813 312 17 : : PUNCT cana-2813 312 18 a a DET cana-2813 312 19 new new ADJ cana-2813 312 20 nature nature NOUN cana-2813 312 21 - - PUNCT cana-2813 312 22 inspired inspire VERB cana-2813 312 23 optimization optimization NOUN cana-2813 312 24 algorithm algorithm NOUN cana-2813 312 25 for for ADP cana-2813 312 26 solving solve VERB cana-2813 312 27 engineering engineering NOUN cana-2813 312 28 problems problem NOUN cana-2813 312 29 , , PUNCT cana-2813 312 30 " " PUNCT cana-2813 312 31 journal journal NOUN cana-2813 312 32 of of ADP cana-2813 312 33 computational computational ADJ cana-2813 312 34 science science NOUN cana-2813 312 35 , , PUNCT cana-2813 312 36 vol vol NOUN cana-2813 312 37 . . PROPN cana-2813 312 38 40 40 NUM cana-2813 312 39 , , PUNCT cana-2813 312 40 pp pp ADJ cana-2813 312 41 . . PUNCT cana-2813 313 1 1141 1141 NUM cana-2813 313 2 - - SYM cana-2813 313 3 1156 1156 NUM cana-2813 313 4 , , PUNCT cana-2813 313 5 2020 2020 NUM cana-2813 313 6 . . PUNCT cana-2813 314 1 doi doi NOUN cana-2813 314 2 : : PUNCT cana-2813 314 3 http://doi.org/10.1016/j.jocs.2019.11.003 http://doi.org/10.1016/j.jocs.2019.11.003 NOUN cana-2813 314 4 [ [ X cana-2813 314 5 26 26 NUM cana-2813 314 6 ] ] X cana-2813 314 7 mirjalili mirjalili NOUN cana-2813 314 8 , , PUNCT cana-2813 314 9 s. s. PROPN cana-2813 314 10 , , PUNCT cana-2813 314 11 " " PUNCT cana-2813 314 12 the the DET cana-2813 314 13 ant ant ADJ cana-2813 314 14 lion lion NOUN cana-2813 314 15 optimizer optimizer NOUN cana-2813 314 16 , , PUNCT cana-2813 314 17 " " PUNCT cana-2813 314 18 advances advance NOUN cana-2813 314 19 in in ADP cana-2813 314 20 engineering engineering NOUN cana-2813 314 21 software software NOUN cana-2813 314 22 , , PUNCT cana-2813 314 23 vol vol NOUN cana-2813 314 24 . . PROPN cana-2813 314 25 83 83 NUM cana-2813 314 26 , , PUNCT cana-2813 314 27 pp pp ADJ cana-2813 314 28 . . PUNCT cana-2813 315 1 7 7 NUM cana-2813 315 2 - - SYM cana-2813 315 3 21 21 NUM cana-2813 315 4 , , PUNCT cana-2813 315 5 2015 2015 NUM cana-2813 315 6 . . PUNCT cana-2813 316 1 doi doi NOUN cana-2813 316 2 : : PUNCT cana-2813 316 3 http://doi.org/10.1016/j.advengsoft.2015.01.010 http://doi.org/10.1016/j.advengsoft.2015.01.010 PROPN cana-2813 316 4 [ [ X cana-2813 316 5 27 27 NUM cana-2813 316 6 ] ] X cana-2813 316 7 elaziz elaziz PROPN cana-2813 316 8 , , PUNCT cana-2813 316 9 m.a m.a PROPN cana-2813 316 10 . . PROPN cana-2813 316 11 , , PUNCT cana-2813 316 12 et et PROPN cana-2813 316 13 al al PROPN cana-2813 316 14 . . PROPN cana-2813 316 15 , , PUNCT cana-2813 316 16 " " PUNCT cana-2813 316 17 a a DET cana-2813 316 18 novel novel ADJ cana-2813 316 19 hybrid hybrid NOUN cana-2813 316 20 method method NOUN cana-2813 316 21 based base VERB cana-2813 316 22 on on ADP cana-2813 316 23 artificial artificial ADJ cana-2813 316 24 bee bee NOUN cana-2813 316 25 colony colony NOUN cana-2813 316 26 and and CCONJ cana-2813 316 27 deep deep ADJ cana-2813 316 28 learning learning NOUN cana-2813 316 29 for for ADP cana-2813 316 30 gene gene NOUN cana-2813 316 31 selection selection NOUN cana-2813 316 32 and and CCONJ cana-2813 316 33 classification classification NOUN cana-2813 316 34 , , PUNCT cana-2813 316 35 " " PUNCT cana-2813 316 36 ieee ieee NOUN cana-2813 316 37 access access NOUN cana-2813 316 38 , , PUNCT cana-2813 316 39 vol vol NOUN cana-2813 316 40 . . PROPN cana-2813 316 41 7 7 NUM cana-2813 316 42 , , PUNCT cana-2813 316 43 pp pp ADJ cana-2813 316 44 . . PUNCT cana-2813 316 45 176809 176809 NUM cana-2813 316 46 - - SYM cana-2813 316 47 176823 176823 NUM cana-2813 316 48 , , PUNCT cana-2813 316 49 2019 2019 NUM cana-2813 316 50 . . PUNCT cana-2813 317 1 doi doi NOUN cana-2813 317 2 : : PUNCT cana-2813 317 3 http://doi.org/10.1109/access.2019.2958250 http://doi.org/10.1109/access.2019.2958250 PROPN cana-2813 318 1 [ [ X cana-2813 318 2 28 28 NUM cana-2813 318 3 ] ] X cana-2813 318 4 zhang zhang PROPN cana-2813 318 5 , , PUNCT cana-2813 318 6 g. g. PROPN cana-2813 318 7 , , PUNCT cana-2813 318 8 et et PROPN cana-2813 318 9 al al PROPN cana-2813 318 10 . . PROPN cana-2813 318 11 , , PUNCT cana-2813 318 12 " " PUNCT cana-2813 318 13 hyperparameter hyperparameter NOUN cana-2813 318 14 optimization optimization NOUN cana-2813 318 15 for for ADP cana-2813 318 16 deep deep ADJ cana-2813 318 17 learning learning NOUN cana-2813 318 18 models model NOUN cana-2813 318 19 with with ADP cana-2813 318 20 bayesian bayesian NOUN cana-2813 318 21 optimization optimization NOUN cana-2813 318 22 , , PUNCT cana-2813 318 23 " " PUNCT cana-2813 318 24 journal journal NOUN cana-2813 318 25 of of ADP cana-2813 318 26 machine machine NOUN cana-2813 318 27 learning learn VERB cana-2813 318 28 research research NOUN cana-2813 318 29 , , PUNCT cana-2813 318 30 vol vol NOUN cana-2813 318 31 . . PROPN cana-2813 318 32 20 20 NUM cana-2813 318 33 , , PUNCT cana-2813 318 34 no no INTJ cana-2813 318 35 . . NOUN cana-2813 318 36 1 1 NUM cana-2813 318 37 , , PUNCT cana-2813 318 38 pp pp ADJ cana-2813 318 39 . . PUNCT cana-2813 319 1 1 1 NUM cana-2813 319 2 - - SYM cana-2813 319 3 15 15 NUM cana-2813 319 4 , , PUNCT cana-2813 319 5 2019 2019 NUM cana-2813 319 6 . . PUNCT cana-2813 320 1 doi doi NOUN cana-2813 320 2 : : PUNCT cana-2813 320 3 http://doi.org/10.1016/j.procs.2020.03.071 http://doi.org/10.1016/j.procs.2020.03.071 PROPN cana-2813 320 4 [ [ X cana-2813 320 5 29 29 NUM cana-2813 320 6 ] ] SYM cana-2813 320 7 li li PROPN cana-2813 320 8 , , PUNCT cana-2813 320 9 x. x. PROPN cana-2813 320 10 , , PUNCT cana-2813 320 11 et et PROPN cana-2813 320 12 al al PROPN cana-2813 320 13 . . PROPN cana-2813 320 14 , , PUNCT cana-2813 320 15 " " PUNCT cana-2813 320 16 gene gene NOUN cana-2813 320 17 expression expression NOUN cana-2813 320 18 data datum NOUN cana-2813 320 19 classification classification NOUN cana-2813 320 20 using use VERB cana-2813 320 21 deep deep ADJ cana-2813 320 22 learning learning NOUN cana-2813 320 23 with with ADP cana-2813 320 24 feature feature NOUN cana-2813 320 25 selection selection NOUN cana-2813 320 26 , , PUNCT cana-2813 320 27 " " PUNCT cana-2813 320 28 scientific scientific ADJ cana-2813 320 29 reports report NOUN cana-2813 320 30 , , PUNCT cana-2813 320 31 vol vol NOUN cana-2813 320 32 . . PROPN cana-2813 321 1 10 10 NUM cana-2813 321 2 , , PUNCT cana-2813 321 3 no no INTJ cana-2813 321 4 . . NOUN cana-2813 321 5 1 1 NUM cana-2813 321 6 , , PUNCT cana-2813 321 7 pp pp ADJ cana-2813 321 8 . . PUNCT cana-2813 322 1 14250 14250 NUM cana-2813 322 2 , , PUNCT cana-2813 322 3 2020 2020 NUM cana-2813 322 4 . . PUNCT cana-2813 323 1 doi doi NOUN cana-2813 323 2 : : PUNCT cana-2813 323 3 http://doi.org/10.1038/s41598-020-71012-x http://doi.org/10.1038/s41598-020-71012-x PROPN cana-2813 324 1 [ [ X cana-2813 324 2 30 30 NUM cana-2813 324 3 ] ] X cana-2813 324 4 wang wang PROPN cana-2813 324 5 , , PUNCT cana-2813 324 6 h. h. PROPN cana-2813 324 7 , , PUNCT cana-2813 324 8 et et PROPN cana-2813 324 9 al al PROPN cana-2813 324 10 . . PROPN cana-2813 324 11 , , PUNCT cana-2813 324 12 " " PUNCT cana-2813 324 13 comparative comparative ADJ cana-2813 324 14 analysis analysis NOUN cana-2813 324 15 of of ADP cana-2813 324 16 deep deep ADJ cana-2813 324 17 learning learning NOUN cana-2813 324 18 and and CCONJ cana-2813 324 19 traditional traditional ADJ cana-2813 324 20 machine machine NOUN cana-2813 324 21 learning learning NOUN cana-2813 324 22 methods method NOUN cana-2813 324 23 for for ADP cana-2813 324 24 gene gene NOUN cana-2813 324 25 expression expression NOUN cana-2813 324 26 data datum NOUN cana-2813 324 27 classification classification NOUN cana-2813 324 28 , , PUNCT cana-2813 324 29 " " PUNCT cana-2813 324 30 bioinformatics bioinformatics NOUN cana-2813 324 31 , , PUNCT cana-2813 324 32 vol vol NOUN cana-2813 324 33 . . PROPN cana-2813 324 34 38 38 NUM cana-2813 324 35 , , PUNCT cana-2813 324 36 no no INTJ cana-2813 324 37 . . NOUN cana-2813 324 38 7 7 NUM cana-2813 324 39 , , PUNCT cana-2813 324 40 pp pp ADJ cana-2813 324 41 . . PUNCT cana-2813 325 1 1891 1891 NUM cana-2813 325 2 - - SYM cana-2813 325 3 1900 1900 NUM cana-2813 325 4 , , PUNCT cana-2813 325 5 2022 2022 NUM cana-2813 325 6 . . PUNCT cana-2813 326 1 doi doi NOUN cana-2813 326 2 : : PUNCT cana-2813 326 3 http://doi.org/10.1093/bioinformatics/btz959 http://doi.org/10.1093/bioinformatics/btz959 NOUN cana-2813 326 4 [ [ X cana-2813 326 5 31 31 NUM cana-2813 326 6 ] ] X cana-2813 326 7 zhou zhou PROPN cana-2813 326 8 , , PUNCT cana-2813 326 9 x. x. PROPN cana-2813 326 10 , , PUNCT cana-2813 326 11 et et PROPN cana-2813 326 12 al al PROPN cana-2813 326 13 . . PROPN cana-2813 326 14 , , PUNCT cana-2813 326 15 " " PUNCT cana-2813 326 16 deep deep ADJ cana-2813 326 17 learning learning NOUN cana-2813 326 18 models model NOUN cana-2813 326 19 for for ADP cana-2813 326 20 genomic genomic ADJ cana-2813 326 21 data datum NOUN cana-2813 326 22 analysis analysis NOUN cana-2813 326 23 and and CCONJ cana-2813 326 24 their their PRON cana-2813 326 25 applications application NOUN cana-2813 326 26 , , PUNCT cana-2813 326 27 " " PUNCT cana-2813 326 28 journal journal NOUN cana-2813 326 29 of of ADP cana-2813 326 30 computational computational ADJ cana-2813 326 31 biology biology NOUN cana-2813 326 32 , , PUNCT cana-2813 326 33 vol vol NOUN cana-2813 326 34 . . PROPN cana-2813 326 35 29 29 NUM cana-2813 326 36 , , PUNCT cana-2813 326 37 no no INTJ cana-2813 326 38 . . NOUN cana-2813 326 39 12 12 NUM cana-2813 326 40 , , PUNCT cana-2813 326 41 pp pp ADJ cana-2813 326 42 . . PUNCT cana-2813 327 1 1606 1606 NUM cana-2813 327 2 - - SYM cana-2813 327 3 1620 1620 NUM cana-2813 327 4 , , PUNCT cana-2813 327 5 2022 2022 NUM cana-2813 327 6 . . PUNCT cana-2813 328 1 doi doi NOUN cana-2813 328 2 : : PUNCT cana-2813 328 3 http://doi.org/10.1089/cmb.2022.0072 http://doi.org/10.1089/cmb.2022.0072 NOUN cana-2813 328 4 [ [ X cana-2813 328 5 32 32 NUM cana-2813 328 6 ] ] PUNCT cana-2813 328 7 zexuan zexuan PROPN cana-2813 328 8 zhu zhu PROPN cana-2813 328 9 , , PUNCT cana-2813 328 10 y. y. PROPN cana-2813 328 11 s. s. PROPN cana-2813 328 12 ong ong PROPN cana-2813 328 13 and and CCONJ cana-2813 328 14 m. m. NOUN cana-2813 328 15 dash dash NOUN cana-2813 328 16 , , PUNCT cana-2813 328 17 β€œ " PUNCT cana-2813 328 18 markov markov NOUN cana-2813 328 19 blanket blanket NOUN cana-2813 328 20 - - PUNCT cana-2813 328 21 embedded embed VERB cana-2813 328 22 genetic genetic ADJ cana-2813 328 23 algorithm algorithm NOUN cana-2813 328 24 for for ADP cana-2813 328 25 gene gene NOUN cana-2813 328 26 selection selection NOUN cana-2813 328 27 , , PUNCT cana-2813 328 28 ” " PUNCT cana-2813 328 29 pattern pattern NOUN cana-2813 328 30 recognition recognition NOUN cana-2813 328 31 , , PUNCT cana-2813 328 32 vol vol NOUN cana-2813 328 33 . . PROPN cana-2813 328 34 49 49 NUM cana-2813 328 35 , , PUNCT cana-2813 328 36 no no INTJ cana-2813 328 37 . . NOUN cana-2813 328 38 11 11 NUM cana-2813 328 39 , , PUNCT cana-2813 328 40 pp pp ADJ cana-2813 328 41 . . PUNCT cana-2813 329 1 3236 3236 NUM cana-2813 329 2 - - SYM cana-2813 329 3 3248 3248 NUM cana-2813 329 4 , , PUNCT cana-2813 329 5 2007 2007 NUM cana-2813 329 6 . . PUNCT cana-2813 330 1 doi doi NOUN cana-2813 330 2 : : PUNCT cana-2813 330 3 http://doi.org/10.1016/j.patcog.2016.06.025 http://doi.org/10.1016/j.patcog.2016.06.025 VERB cana-2813 330 4 [ [ PUNCT cana-2813 330 5 33 33 NUM cana-2813 330 6 ] ] PUNCT cana-2813 330 7 yanrong yanrong PROPN cana-2813 330 8 ji ji PROPN cana-2813 330 9 , , PUNCT cana-2813 330 10 zhihan zhihan PROPN cana-2813 330 11 zhou zhou PROPN cana-2813 330 12 , , PUNCT cana-2813 330 13 han han PROPN cana-2813 330 14 liu liu PROPN cana-2813 330 15 , , PUNCT cana-2813 330 16 ramana ramana PROPN cana-2813 330 17 v v ADP cana-2813 330 18 davuluri davuluri NOUN cana-2813 330 19 , , PUNCT cana-2813 330 20 dnabert dnabert NOUN cana-2813 330 21 : : PUNCT cana-2813 330 22 pre pre ADJ cana-2813 330 23 - - ADJ cana-2813 330 24 trained train VERB cana-2813 330 25 bidirectional bidirectional ADJ cana-2813 330 26 encoder encoder NOUN cana-2813 330 27 representations representation VERB cana-2813 330 28 from from ADP cana-2813 330 29 transformers transformer NOUN cana-2813 330 30 model model NOUN cana-2813 330 31 for for ADP cana-2813 330 32 dna dna NOUN cana-2813 330 33 - - PUNCT cana-2813 330 34 language language NOUN cana-2813 330 35 in in ADP cana-2813 330 36 genome genome NOUN cana-2813 330 37 , , PUNCT cana-2813 330 38 bioinformatics bioinformatics NOUN cana-2813 330 39 , , PUNCT cana-2813 330 40 volume volume NOUN cana-2813 330 41 37 37 NUM cana-2813 330 42 , , PUNCT cana-2813 330 43 issue issue NOUN cana-2813 330 44 15 15 NUM cana-2813 330 45 , , PUNCT cana-2813 330 46 august august PROPN cana-2813 330 47 2021 2021 NUM cana-2813 330 48 , , PUNCT cana-2813 330 49 pages page NOUN cana-2813 330 50 2112–2120 2112–2120 NUM cana-2813 330 51 , , PUNCT cana-2813 330 52 https://doi.org/10.1093/bioinformatics/btab083 https://doi.org/10.1093/bioinformatics/btab083 PROPN cana-2813 330 53 http://doi.org/10.1162/neco.1997.9.8.1735 http://doi.org/10.1162/neco.1997.9.8.1735 VERB cana-2813 330 54 http://doi.org/10.1089/cmb.2015.0232 http://doi.org/10.1089/cmb.2015.0232 PROPN cana-2813 330 55 http://doi.org/10.1093/bioinformatics/btaa741 http://doi.org/10.1093/bioinformatics/btaa741 PROPN cana-2813 330 56 http://doi.org/10.1007/s00500-015-1865-0 http://doi.org/10.1007/s00500-015-1865-0 NUM cana-2813 330 57 http://doi.org/10.1109/icnn.1995.488968 http://doi.org/10.1109/icnn.1995.488968 PROPN cana-2813 330 58 http://doi.org/10.1162/evco_a_00009 http://doi.org/10.1162/evco_a_00009 X cana-2813 331 1 http://doi.org/10.1109/tbme.2015.2500184 http://doi.org/10.1109/tbme.2015.2500184 PROPN cana-2813 331 2 http://doi.org/10.48550/arxiv.1706.03762 http://doi.org/10.48550/arxiv.1706.03762 PROPN cana-2813 331 3 http://doi.org/10.1016/j.jocs.2019.11.003 http://doi.org/10.1016/j.jocs.2019.11.003 NOUN cana-2813 331 4 http://doi.org/10.1016/j.advengsoft.2015.01.010 http://doi.org/10.1016/j.advengsoft.2015.01.010 PROPN cana-2813 331 5 http://doi.org/10.1109/access.2019.2958250 http://doi.org/10.1109/access.2019.2958250 PROPN cana-2813 331 6 http://doi.org/10.1016/j.procs.2020.03.071 http://doi.org/10.1016/j.procs.2020.03.071 ADJ cana-2813 331 7 http://doi.org/10.1038/s41598-020-71012-x http://doi.org/10.1038/s41598-020-71012-x NOUN cana-2813 331 8 http://doi.org/10.1089/cmb.2022.0072 http://doi.org/10.1089/cmb.2022.0072 ADV cana-2813 331 9 http://doi.org/10.1016/j.patcog.2016.06.025 http://doi.org/10.1016/j.patcog.2016.06.025 VERB cana-2813 331 10 https://doi.org/10.1093/bioinformatics/btab083 https://doi.org/10.1093/bioinformatics/btab083 X