id	sid	tid	token	lemma	pos
admet-1335	1	1	proall	proall	NOUN
admet-1335	1	2	-	-	PUNCT
admet-1335	1	3	d	d	NOUN
admet-1335	1	4	:	:	PUNCT
admet-1335	1	5	protein	protein	NOUN
admet-1335	1	6	allergen	allergen	NOUN
admet-1335	1	7	detection	detection	NOUN
admet-1335	1	8	using	use	VERB
admet-1335	1	9	long	long	ADJ
admet-1335	1	10	short	short	ADJ
admet-1335	1	11	term	term	NOUN
admet-1335	1	12	memory	memory	NOUN
admet-1335	1	13	a	a	DET
admet-1335	1	14	deep	deep	ADJ
admet-1335	1	15	learning	learning	NOUN
admet-1335	1	16	approach	approach	NOUN
admet-1335	1	17	doi	doi	NOUN
admet-1335	1	18	:	:	PUNCT
admet-1335	1	19	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	1	20	231	231	NUM
admet-1335	1	21	admet	admet	X
admet-1335	1	22	&	&	CCONJ
admet-1335	1	23	dmpk	dmpk	PROPN
admet-1335	1	24	10(3	10(3	NUM
admet-1335	1	25	)	)	PUNCT
admet-1335	1	26	(	(	PUNCT
admet-1335	1	27	2022	2022	NUM
admet-1335	1	28	)	)	PUNCT
admet-1335	1	29	231	231	NUM
admet-1335	1	30	-	-	SYM
admet-1335	1	31	240	240	NUM
admet-1335	1	32	;	;	PUNCT
admet-1335	1	33	doi	doi	NOUN
admet-1335	1	34	:	:	PUNCT
admet-1335	1	35	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	1	36	open	open	ADJ
admet-1335	1	37	access	access	NOUN
admet-1335	1	38	:	:	PUNCT
admet-1335	1	39	issn	issn	PROPN
admet-1335	1	40	:	:	PUNCT
admet-1335	1	41	1848	1848	NUM
admet-1335	1	42	-	-	SYM
admet-1335	1	43	7718	7718	NUM
admet-1335	1	44	http://www.pub.iapchem.org/ojs/index.php/admet/index	http://www.pub.iapchem.org/ojs/index.php/admet/index	NOUN
admet-1335	1	45	original	original	ADJ
admet-1335	1	46	scientific	scientific	ADJ
admet-1335	1	47	paper	paper	NOUN
admet-1335	1	48	proall	proall	NOUN
admet-1335	1	49	-	-	PUNCT
admet-1335	1	50	d	d	NOUN
admet-1335	1	51	:	:	PUNCT
admet-1335	1	52	protein	protein	NOUN
admet-1335	1	53	allergen	allergen	NOUN
admet-1335	1	54	detection	detection	NOUN
admet-1335	1	55	using	use	VERB
admet-1335	1	56	long	long	ADJ
admet-1335	1	57	short	short	ADJ
admet-1335	1	58	term	term	NOUN
admet-1335	1	59	memory	memory	NOUN
admet-1335	1	60	a	a	DET
admet-1335	1	61	deep	deep	ADJ
admet-1335	1	62	learning	learning	NOUN
admet-1335	1	63	approach	approach	NOUN
admet-1335	1	64	pallavi	pallavi	PROPN
admet-1335	1	65	m.	m.	PROPN
admet-1335	1	66	shanthappa	shanthappa	PROPN
admet-1335	1	67	*	*	PROPN
admet-1335	1	68	,	,	PUNCT
admet-1335	1	69	rakshitha	rakshitha	PROPN
admet-1335	1	70	kumar	kumar	PROPN
admet-1335	1	71	*	*	PROPN
admet-1335	1	72	department	department	PROPN
admet-1335	1	73	of	of	ADP
admet-1335	1	74	computer	computer	NOUN
admet-1335	1	75	science	science	NOUN
admet-1335	1	76	,	,	PUNCT
admet-1335	1	77	amrita	amrita	PROPN
admet-1335	1	78	school	school	PROPN
admet-1335	1	79	of	of	ADP
admet-1335	1	80	arts	art	NOUN
admet-1335	1	81	and	and	CCONJ
admet-1335	1	82	sciences	science	NOUN
admet-1335	1	83	,	,	PUNCT
admet-1335	1	84	mysuru	mysuru	NOUN
admet-1335	1	85	campus	campus	NOUN
admet-1335	1	86	,	,	PUNCT
admet-1335	1	87	amrita	amrita	PROPN
admet-1335	1	88	vishwa	vishwa	PROPN
admet-1335	1	89	vidyapeetham	vidyapeetham	PROPN
admet-1335	1	90	,	,	PUNCT
admet-1335	1	91	india	india	PROPN
admet-1335	1	92	*	*	PUNCT
admet-1335	1	93	corresponding	correspond	VERB
admet-1335	1	94	authors	author	NOUN
admet-1335	1	95	:	:	PUNCT
admet-1335	1	96	e	e	X
admet-1335	1	97	-	-	NOUN
admet-1335	1	98	mail	mail	NOUN
admet-1335	1	99	:	:	PUNCT
admet-1335	1	100	palls.ms@gmail.com	palls.ms@gmail.com	PROPN
admet-1335	1	101	;	;	PUNCT
admet-1335	1	102	rakshitha.k.k1999@gmail.com	rakshitha.k.k1999@gmail.com	PROPN
admet-1335	1	103	.	.	PROPN
admet-1335	1	104	received	receive	VERB
admet-1335	1	105	:	:	PUNCT
admet-1335	1	106	april	april	PROPN
admet-1335	1	107	03	03	NUM
admet-1335	1	108	,	,	PUNCT
admet-1335	1	109	2022	2022	NUM
admet-1335	1	110	;	;	PUNCT
admet-1335	1	111	revised	revise	VERB
admet-1335	1	112	:	:	PUNCT
admet-1335	1	113	july	july	PROPN
admet-1335	1	114	15	15	NUM
admet-1335	1	115	,	,	PUNCT
admet-1335	1	116	2022	2022	NUM
admet-1335	1	117	;	;	PUNCT
admet-1335	1	118	available	available	ADJ
admet-1335	1	119	online	online	NOUN
admet-1335	1	120	:	:	PUNCT
admet-1335	1	121	august	august	PROPN
admet-1335	1	122	21	21	NUM
admet-1335	1	123	,	,	PUNCT
admet-1335	1	124	2022	2022	NUM
admet-1335	1	125	abstract	abstract	ADJ
admet-1335	1	126	background	background	NOUN
admet-1335	1	127	:	:	PUNCT
admet-1335	1	128	an	an	DET
admet-1335	1	129	allergic	allergic	ADJ
admet-1335	1	130	reaction	reaction	NOUN
admet-1335	1	131	is	be	AUX
admet-1335	1	132	the	the	DET
admet-1335	1	133	immune	immune	ADJ
admet-1335	1	134	system	system	NOUN
admet-1335	1	135	's	's	PART
admet-1335	1	136	overreacting	overreact	VERB
admet-1335	1	137	to	to	ADP
admet-1335	1	138	a	a	DET
admet-1335	1	139	previously	previously	ADV
admet-1335	1	140	encountered	encounter	VERB
admet-1335	1	141	,	,	PUNCT
admet-1335	1	142	typically	typically	ADV
admet-1335	1	143	benign	benign	ADJ
admet-1335	1	144	molecule	molecule	NOUN
admet-1335	1	145	,	,	PUNCT
admet-1335	1	146	frequently	frequently	ADV
admet-1335	1	147	a	a	DET
admet-1335	1	148	protein	protein	NOUN
admet-1335	1	149	.	.	PUNCT
admet-1335	2	1	allergy	allergy	NOUN
admet-1335	2	2	reactions	reaction	NOUN
admet-1335	2	3	can	can	AUX
admet-1335	2	4	result	result	VERB
admet-1335	2	5	in	in	ADP
admet-1335	2	6	rashes	rash	NOUN
admet-1335	2	7	,	,	PUNCT
admet-1335	2	8	itching	itching	NOUN
admet-1335	2	9	,	,	PUNCT
admet-1335	2	10	mucous	mucous	ADJ
admet-1335	2	11	membrane	membrane	NOUN
admet-1335	2	12	swelling	swelling	NOUN
admet-1335	2	13	,	,	PUNCT
admet-1335	2	14	asthma	asthma	NOUN
admet-1335	2	15	,	,	PUNCT
admet-1335	2	16	coughing	cough	VERB
admet-1335	2	17	,	,	PUNCT
admet-1335	2	18	and	and	CCONJ
admet-1335	2	19	other	other	ADJ
admet-1335	2	20	bizarre	bizarre	ADJ
admet-1335	2	21	symptoms	symptom	NOUN
admet-1335	2	22	.	.	PUNCT
admet-1335	3	1	to	to	PART
admet-1335	3	2	anticipate	anticipate	VERB
admet-1335	3	3	allergies	allergy	NOUN
admet-1335	3	4	,	,	PUNCT
admet-1335	3	5	a	a	DET
admet-1335	3	6	wide	wide	ADJ
admet-1335	3	7	range	range	NOUN
admet-1335	3	8	of	of	ADP
admet-1335	3	9	principles	principle	NOUN
admet-1335	3	10	and	and	CCONJ
admet-1335	3	11	methods	method	NOUN
admet-1335	3	12	have	have	AUX
admet-1335	3	13	been	be	AUX
admet-1335	3	14	applied	apply	VERB
admet-1335	3	15	in	in	ADP
admet-1335	3	16	bioinformatics	bioinformatics	NOUN
admet-1335	3	17	.	.	PUNCT
admet-1335	4	1	the	the	DET
admet-1335	4	2	sequence	sequence	NOUN
admet-1335	4	3	similarity	similarity	NOUN
admet-1335	4	4	approach	approach	NOUN
admet-1335	4	5	's	's	PART
admet-1335	4	6	positive	positive	ADJ
admet-1335	4	7	predictive	predictive	ADJ
admet-1335	4	8	value	value	NOUN
admet-1335	4	9	is	be	AUX
admet-1335	4	10	very	very	ADV
admet-1335	4	11	low	low	ADJ
admet-1335	4	12	and	and	CCONJ
admet-1335	4	13	ineffective	ineffective	ADJ
admet-1335	4	14	for	for	ADP
admet-1335	4	15	methods	method	NOUN
admet-1335	4	16	based	base	VERB
admet-1335	4	17	on	on	ADP
admet-1335	4	18	fao	fao	PROPN
admet-1335	4	19	/	/	SYM
admet-1335	4	20	who	who	PRON
admet-1335	4	21	criteria	criteria	VERB
admet-1335	4	22	,	,	PUNCT
admet-1335	4	23	making	make	VERB
admet-1335	4	24	it	it	PRON
admet-1335	4	25	difficult	difficult	ADJ
admet-1335	4	26	to	to	PART
admet-1335	4	27	predict	predict	VERB
admet-1335	4	28	possible	possible	ADJ
admet-1335	4	29	allergens	allergen	NOUN
admet-1335	4	30	.	.	PUNCT
admet-1335	5	1	method	method	NOUN
admet-1335	5	2	:	:	PUNCT
admet-1335	5	3	this	this	DET
admet-1335	5	4	work	work	NOUN
admet-1335	5	5	advocated	advocate	VERB
admet-1335	5	6	the	the	DET
admet-1335	5	7	use	use	NOUN
admet-1335	5	8	of	of	ADP
admet-1335	5	9	a	a	DET
admet-1335	5	10	deep	deep	ADJ
admet-1335	5	11	learning	learning	NOUN
admet-1335	5	12	model	model	NOUN
admet-1335	5	13	lstm	lstm	PROPN
admet-1335	5	14	(	(	PUNCT
admet-1335	5	15	long	long	ADJ
admet-1335	5	16	short	short	ADJ
admet-1335	5	17	-	-	PUNCT
admet-1335	5	18	term	term	NOUN
admet-1335	5	19	memory	memory	NOUN
admet-1335	5	20	)	)	PUNCT
admet-1335	5	21	to	to	PART
admet-1335	5	22	overcome	overcome	VERB
admet-1335	5	23	the	the	DET
admet-1335	5	24	limitations	limitation	NOUN
admet-1335	5	25	of	of	ADP
admet-1335	5	26	traditional	traditional	ADJ
admet-1335	5	27	approaches	approach	NOUN
admet-1335	5	28	and	and	CCONJ
admet-1335	5	29	machine	machine	NOUN
admet-1335	5	30	learning	learn	VERB
admet-1335	5	31	lower	low	ADJ
admet-1335	5	32	performance	performance	NOUN
admet-1335	5	33	models	model	NOUN
admet-1335	5	34	in	in	ADP
admet-1335	5	35	predicting	predict	VERB
admet-1335	5	36	the	the	DET
admet-1335	5	37	allergenicity	allergenicity	NOUN
admet-1335	5	38	of	of	ADP
admet-1335	5	39	dietary	dietary	ADJ
admet-1335	5	40	proteins	protein	NOUN
admet-1335	5	41	.	.	PUNCT
admet-1335	6	1	a	a	DET
admet-1335	6	2	total	total	NOUN
admet-1335	6	3	of	of	ADP
admet-1335	6	4	2,427	2,427	NUM
admet-1335	6	5	allergens	allergen	NOUN
admet-1335	6	6	and	and	CCONJ
admet-1335	6	7	2,427	2,427	NUM
admet-1335	6	8	non	non	NOUN
admet-1335	6	9	-	-	NOUN
admet-1335	6	10	allergens	allergen	NOUN
admet-1335	6	11	,	,	PUNCT
admet-1335	6	12	from	from	ADP
admet-1335	6	13	a	a	DET
admet-1335	6	14	variety	variety	NOUN
admet-1335	6	15	of	of	ADP
admet-1335	6	16	sources	source	NOUN
admet-1335	6	17	,	,	PUNCT
admet-1335	6	18	including	include	VERB
admet-1335	6	19	the	the	DET
admet-1335	6	20	central	central	ADJ
admet-1335	6	21	science	science	NOUN
admet-1335	6	22	laboratory	laboratory	NOUN
admet-1335	6	23	and	and	CCONJ
admet-1335	6	24	the	the	DET
admet-1335	6	25	ncbi	ncbi	NOUN
admet-1335	6	26	are	be	AUX
admet-1335	6	27	used	use	VERB
admet-1335	6	28	.	.	PUNCT
admet-1335	7	1	the	the	DET
admet-1335	7	2	data	datum	NOUN
admet-1335	7	3	was	be	AUX
admet-1335	7	4	divided	divide	VERB
admet-1335	7	5	80:20	80:20	NUM
admet-1335	7	6	for	for	ADP
admet-1335	7	7	training	training	NOUN
admet-1335	7	8	and	and	CCONJ
admet-1335	7	9	testing	testing	NOUN
admet-1335	7	10	purposes	purpose	NOUN
admet-1335	7	11	.	.	PUNCT
admet-1335	8	1	these	these	DET
admet-1335	8	2	techniques	technique	NOUN
admet-1335	8	3	have	have	AUX
admet-1335	8	4	all	all	PRON
admet-1335	8	5	been	be	AUX
admet-1335	8	6	implemented	implement	VERB
admet-1335	8	7	in	in	ADP
admet-1335	8	8	python	python	NOUN
admet-1335	8	9	.	.	PUNCT
admet-1335	9	1	to	to	PART
admet-1335	9	2	describe	describe	VERB
admet-1335	9	3	the	the	DET
admet-1335	9	4	protein	protein	NOUN
admet-1335	9	5	sequences	sequence	NOUN
admet-1335	9	6	of	of	ADP
admet-1335	9	7	allergens	allergen	NOUN
admet-1335	9	8	and	and	CCONJ
admet-1335	9	9	non	non	NOUN
admet-1335	9	10	-	-	NOUN
admet-1335	9	11	allergens	allergen	NOUN
admet-1335	9	12	,	,	PUNCT
admet-1335	9	13	five	five	NUM
admet-1335	9	14	e	e	NOUN
admet-1335	9	15	-	-	NOUN
admet-1335	9	16	descriptors	descriptor	NOUN
admet-1335	9	17	were	be	AUX
admet-1335	9	18	used	use	VERB
admet-1335	9	19	.	.	PUNCT
admet-1335	10	1	e1	e1	NOUN
admet-1335	10	2	(	(	PUNCT
admet-1335	10	3	hydrophilic	hydrophilic	ADJ
admet-1335	10	4	character	character	NOUN
admet-1335	10	5	of	of	ADP
admet-1335	10	6	peptides	peptide	NOUN
admet-1335	10	7	)	)	PUNCT
admet-1335	10	8	,	,	PUNCT
admet-1335	10	9	e2	e2	PROPN
admet-1335	10	10	(	(	PUNCT
admet-1335	10	11	length	length	NOUN
admet-1335	10	12	)	)	PUNCT
admet-1335	10	13	,	,	PUNCT
admet-1335	10	14	e3(propensity	e3(propensity	NOUN
admet-1335	10	15	to	to	PART
admet-1335	10	16	form	form	VERB
admet-1335	10	17	helices	helix	NOUN
admet-1335	10	18	)	)	PUNCT
admet-1335	10	19	,	,	PUNCT
admet-1335	10	20	e4(abundance	e4(abundance	NOUN
admet-1335	10	21	and	and	CCONJ
admet-1335	10	22	dispersion	dispersion	NOUN
admet-1335	10	23	)	)	PUNCT
admet-1335	10	24	,	,	PUNCT
admet-1335	10	25	and	and	CCONJ
admet-1335	10	26	e5	e5	PROPN
admet-1335	10	27	(	(	PUNCT
admet-1335	10	28	propensity	propensity	NOUN
admet-1335	10	29	of	of	ADP
admet-1335	10	30	beta	beta	ADJ
admet-1335	10	31	strands	strand	NOUN
admet-1335	10	32	)	)	PUNCT
admet-1335	10	33	are	be	AUX
admet-1335	10	34	used	use	VERB
admet-1335	10	35	to	to	PART
admet-1335	10	36	make	make	VERB
admet-1335	10	37	the	the	DET
admet-1335	10	38	variable	variable	ADJ
admet-1335	10	39	-	-	PUNCT
admet-1335	10	40	length	length	NOUN
admet-1335	10	41	protein	protein	NOUN
admet-1335	10	42	sequence	sequence	NOUN
admet-1335	10	43	to	to	PART
admet-1335	10	44	uniform	uniform	ADJ
admet-1335	10	45	length	length	NOUN
admet-1335	10	46	using	use	VERB
admet-1335	10	47	acc	acc	PROPN
admet-1335	10	48	transformation	transformation	NOUN
admet-1335	10	49	.	.	PUNCT
admet-1335	11	1	a	a	DET
admet-1335	11	2	total	total	NOUN
admet-1335	11	3	of	of	ADP
admet-1335	11	4	eight	eight	NUM
admet-1335	11	5	machine	machine	NOUN
admet-1335	11	6	learning	learn	VERB
admet-1335	11	7	techniques	technique	NOUN
admet-1335	11	8	have	have	AUX
admet-1335	11	9	been	be	AUX
admet-1335	11	10	taken	take	VERB
admet-1335	11	11	into	into	ADP
admet-1335	11	12	consideration	consideration	NOUN
admet-1335	11	13	.	.	PUNCT
admet-1335	12	1	results	result	NOUN
admet-1335	12	2	:	:	PUNCT
admet-1335	12	3	the	the	DET
admet-1335	12	4	gaussian	gaussian	ADJ
admet-1335	12	5	naive	naive	ADJ
admet-1335	12	6	bayes	bayes	NOUN
admet-1335	12	7	as	as	ADP
admet-1335	12	8	accuracy	accuracy	NOUN
admet-1335	12	9	of	of	ADP
admet-1335	12	10	64.14	64.14	NUM
admet-1335	12	11	%	%	NOUN
admet-1335	12	12	,	,	PUNCT
admet-1335	12	13	radius	radius	NOUN
admet-1335	12	14	neighbour	neighbour	NOUN
admet-1335	12	15	's	's	PART
admet-1335	12	16	classifier	classifier	NOUN
admet-1335	12	17	with	with	ADP
admet-1335	12	18	49.2	49.2	NUM
admet-1335	12	19	%	%	NOUN
admet-1335	12	20	,	,	PUNCT
admet-1335	12	21	bagging	bagging	NOUN
admet-1335	12	22	classifier	classifier	NOUN
admet-1335	12	23	was	be	AUX
admet-1335	12	24	85.8	85.8	NUM
admet-1335	12	25	%	%	NOUN
admet-1335	12	26	,	,	PUNCT
admet-1335	12	27	ada	ada	PROPN
admet-1335	12	28	boost	boost	PROPN
admet-1335	12	29	was	be	AUX
admet-1335	12	30	76.9	76.9	NUM
admet-1335	12	31	%	%	NOUN
admet-1335	12	32	,	,	PUNCT
admet-1335	12	33	linear	linear	ADJ
admet-1335	12	34	discriminant	discriminant	ADJ
admet-1335	12	35	analysis	analysis	NOUN
admet-1335	12	36	has	have	VERB
admet-1335	12	37	76.13	76.13	NUM
admet-1335	12	38	%	%	NOUN
admet-1335	12	39	,	,	PUNCT
admet-1335	12	40	quadratic	quadratic	ADJ
admet-1335	12	41	discriminant	discriminant	ADJ
admet-1335	12	42	analysis	analysis	NOUN
admet-1335	12	43	was	be	AUX
admet-1335	12	44	84.2	84.2	NUM
admet-1335	12	45	%	%	NOUN
admet-1335	12	46	,	,	PUNCT
admet-1335	12	47	extra	extra	ADJ
admet-1335	12	48	tree	tree	NOUN
admet-1335	12	49	classifier	classifier	NOUN
admet-1335	12	50	was	be	AUX
admet-1335	12	51	90	90	NUM
admet-1335	12	52	%	%	NOUN
admet-1335	12	53	,	,	PUNCT
admet-1335	12	54	and	and	CCONJ
admet-1335	12	55	lstm	lstm	NOUN
admet-1335	12	56	is	be	AUX
admet-1335	12	57	91.5	91.5	NUM
admet-1335	12	58	%	%	NOUN
admet-1335	12	59	.	.	PUNCT
admet-1335	13	1	conclusion	conclusion	NOUN
admet-1335	13	2	:	:	PUNCT
admet-1335	13	3	as	as	ADP
admet-1335	13	4	the	the	DET
admet-1335	13	5	lstm	lstm	NOUN
admet-1335	13	6	,	,	PUNCT
admet-1335	13	7	has	have	VERB
admet-1335	13	8	an	an	DET
admet-1335	13	9	auc	auc	ADJ
admet-1335	13	10	value	value	NOUN
admet-1335	13	11	of	of	ADP
admet-1335	13	12	91.5	91.5	NUM
admet-1335	13	13	%	%	NOUN
admet-1335	13	14	is	be	AUX
admet-1335	13	15	regarded	regard	VERB
admet-1335	13	16	best	good	ADJ
admet-1335	13	17	in	in	ADP
admet-1335	13	18	predicting	predict	VERB
admet-1335	13	19	allergens	allergen	NOUN
admet-1335	13	20	.	.	PUNCT
admet-1335	14	1	a	a	DET
admet-1335	14	2	web	web	NOUN
admet-1335	14	3	server	server	NOUN
admet-1335	14	4	called	call	VERB
admet-1335	14	5	proall	proall	NOUN
admet-1335	14	6	-	-	PUNCT
admet-1335	14	7	d	d	PROPN
admet-1335	14	8	has	have	AUX
admet-1335	14	9	been	be	AUX
admet-1335	14	10	created	create	VERB
admet-1335	14	11	that	that	SCONJ
admet-1335	14	12	successfully	successfully	ADV
admet-1335	14	13	identifies	identify	VERB
admet-1335	14	14	novel	novel	ADJ
admet-1335	14	15	allergens	allergen	NOUN
admet-1335	14	16	using	use	VERB
admet-1335	14	17	the	the	DET
admet-1335	14	18	lstm	lstm	NOUN
admet-1335	14	19	approach	approach	NOUN
admet-1335	14	20	.	.	PUNCT
admet-1335	15	1	users	user	NOUN
admet-1335	15	2	can	can	AUX
admet-1335	15	3	use	use	VERB
admet-1335	15	4	the	the	DET
admet-1335	15	5	link	link	NOUN
admet-1335	15	6	https://doi.org/10.17632/tjmt97xpjf.1	https://doi.org/10.17632/tjmt97xpjf.1	NOUN
admet-1335	15	7	to	to	PART
admet-1335	15	8	access	access	VERB
admet-1335	15	9	the	the	DET
admet-1335	15	10	proall	proall	ADJ
admet-1335	15	11	-	-	PUNCT
admet-1335	15	12	d	d	NOUN
admet-1335	15	13	server	server	NOUN
admet-1335	15	14	and	and	CCONJ
admet-1335	15	15	data	datum	NOUN
admet-1335	15	16	.	.	PUNCT
admet-1335	16	1	©	©	X
admet-1335	16	2	2022	2022	NUM
admet-1335	16	3	by	by	ADP
admet-1335	16	4	the	the	DET
admet-1335	16	5	authors	author	NOUN
admet-1335	16	6	.	.	PUNCT
admet-1335	17	1	this	this	DET
admet-1335	17	2	article	article	NOUN
admet-1335	17	3	is	be	AUX
admet-1335	17	4	an	an	DET
admet-1335	17	5	open	open	ADJ
admet-1335	17	6	-	-	PUNCT
admet-1335	17	7	access	access	NOUN
admet-1335	17	8	article	article	NOUN
admet-1335	17	9	distributed	distribute	VERB
admet-1335	17	10	under	under	ADP
admet-1335	17	11	the	the	DET
admet-1335	17	12	terms	term	NOUN
admet-1335	17	13	and	and	CCONJ
admet-1335	17	14	conditions	condition	NOUN
admet-1335	17	15	of	of	ADP
admet-1335	17	16	the	the	DET
admet-1335	17	17	creative	creative	ADJ
admet-1335	17	18	commons	common	NOUN
admet-1335	17	19	attribution	attribution	NOUN
admet-1335	17	20	license	license	NOUN
admet-1335	17	21	(	(	PUNCT
admet-1335	17	22	http://creativecommons.org/licenses/by/4.0/	http://creativecommons.org/licenses/by/4.0/	PROPN
admet-1335	17	23	)	)	PUNCT
admet-1335	17	24	.	.	PUNCT
admet-1335	18	1	keywords	keyword	NOUN
admet-1335	18	2	allergen	allergen	VERB
admet-1335	18	3	prediction	prediction	NOUN
admet-1335	18	4	;	;	PUNCT
admet-1335	18	5	acc	acc	PROPN
admet-1335	18	6	transformation	transformation	NOUN
admet-1335	18	7	;	;	PUNCT
admet-1335	18	8	lstm	lstm	NOUN
admet-1335	18	9	model	model	NOUN
admet-1335	18	10	;	;	PUNCT
admet-1335	18	11	gaussian	gaussian	ADJ
admet-1335	18	12	naive	naive	ADJ
admet-1335	18	13	bayes	bayes	NOUN
admet-1335	18	14	;	;	PUNCT
admet-1335	18	15	classifier	classifier	NOUN
admet-1335	18	16	;	;	PUNCT
admet-1335	18	17	extra	extra	ADJ
admet-1335	18	18	tree	tree	NOUN
admet-1335	18	19	classifier	classifier	NOUN
admet-1335	18	20	;	;	PUNCT
admet-1335	18	21	bagging	bag	VERB
admet-1335	18	22	classifier	classifier	NOUN
admet-1335	18	23	;	;	PUNCT
admet-1335	18	24	ada	ada	PROPN
admet-1335	18	25	boost	boost	PROPN
admet-1335	18	26	;	;	PUNCT
admet-1335	18	27	linear	linear	ADJ
admet-1335	18	28	discriminant	discriminant	ADJ
admet-1335	18	29	analysis	analysis	NOUN
admet-1335	18	30	;	;	PUNCT
admet-1335	18	31	quadratic	quadratic	ADJ
admet-1335	18	32	discriminant	discriminant	ADJ
admet-1335	18	33	analysis	analysis	NOUN
admet-1335	18	34	introduction	introduction	NOUN
admet-1335	18	35	allergy	allergy	NOUN
admet-1335	18	36	,	,	PUNCT
admet-1335	18	37	often	often	ADV
admet-1335	18	38	described	describe	VERB
admet-1335	18	39	as	as	ADP
admet-1335	18	40	an	an	DET
admet-1335	18	41	autoimmune	autoimmune	ADJ
admet-1335	18	42	disorder	disorder	NOUN
admet-1335	18	43	,	,	PUNCT
admet-1335	18	44	is	be	AUX
admet-1335	18	45	a	a	DET
admet-1335	18	46	clinical	clinical	ADJ
admet-1335	18	47	condition	condition	NOUN
admet-1335	18	48	characterized	characterize	VERB
admet-1335	18	49	by	by	ADP
admet-1335	18	50	the	the	DET
admet-1335	18	51	immune	immune	ADJ
admet-1335	18	52	system	system	NOUN
admet-1335	18	53	’s	’s	PART
admet-1335	18	54	sensitivity	sensitivity	NOUN
admet-1335	18	55	to	to	ADP
admet-1335	18	56	normally	normally	ADV
admet-1335	18	57	innocuous	innocuous	ADJ
admet-1335	18	58	elements	element	NOUN
admet-1335	18	59	.	.	PUNCT
admet-1335	19	1	the	the	DET
admet-1335	19	2	substance	substance	NOUN
admet-1335	19	3	that	that	PRON
admet-1335	19	4	causes	cause	VERB
admet-1335	19	5	allergy	allergy	NOUN
admet-1335	19	6	is	be	AUX
admet-1335	19	7	known	know	VERB
admet-1335	19	8	as	as	ADP
admet-1335	19	9	an	an	DET
admet-1335	19	10	allergen	allergen	NOUN
admet-1335	19	11	.	.	PUNCT
admet-1335	20	1	allergens	allergen	NOUN
admet-1335	20	2	can	can	AUX
admet-1335	20	3	be	be	AUX
admet-1335	20	4	dust	dust	NOUN
admet-1335	20	5	,	,	PUNCT
admet-1335	20	6	pollen	pollen	NOUN
admet-1335	20	7	,	,	PUNCT
admet-1335	20	8	cosmetics	cosmetic	NOUN
admet-1335	20	9	,	,	PUNCT
admet-1335	20	10	and	and	CCONJ
admet-1335	20	11	food	food	NOUN
admet-1335	20	12	.	.	PUNCT
admet-1335	21	1	in	in	ADP
admet-1335	21	2	food	food	NOUN
admet-1335	21	3	,	,	PUNCT
admet-1335	21	4	allergy	allergy	NOUN
admet-1335	21	5	is	be	AUX
admet-1335	21	6	usually	usually	ADV
admet-1335	21	7	caused	cause	VERB
admet-1335	21	8	by	by	ADP
admet-1335	21	9	proteins	protein	NOUN
admet-1335	21	10	.	.	PUNCT
admet-1335	22	1	proteins	protein	NOUN
admet-1335	22	2	are	be	AUX
admet-1335	22	3	an	an	DET
admet-1335	22	4	essential	essential	ADJ
admet-1335	22	5	part	part	NOUN
admet-1335	22	6	of	of	ADP
admet-1335	22	7	our	our	PRON
admet-1335	22	8	diet	diet	NOUN
admet-1335	22	9	,	,	PUNCT
admet-1335	22	10	but	but	CCONJ
admet-1335	22	11	some	some	DET
admet-1335	22	12	proteins	protein	NOUN
admet-1335	22	13	can	can	AUX
admet-1335	22	14	also	also	ADV
admet-1335	22	15	be	be	AUX
admet-1335	22	16	harmful	harmful	ADJ
admet-1335	22	17	to	to	ADP
admet-1335	22	18	some	some	DET
admet-1335	22	19	individuals	individual	NOUN
admet-1335	22	20	.	.	PUNCT
admet-1335	23	1	one	one	NUM
admet-1335	23	2	of	of	ADP
admet-1335	23	3	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	23	4	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	23	5	http://www.pub.iapchem.org/ojs/index.php/admet/index	http://www.pub.iapchem.org/ojs/index.php/admet/index	NOUN
admet-1335	23	6	mailto:palls.ms@gmail.com	mailto:palls.ms@gmail.com	PROPN
admet-1335	23	7	mailto:rakshitha.k.k1999@gmail.com	mailto:rakshitha.k.k1999@gmail.com	PROPN
admet-1335	23	8	https://doi.org/10.17632/tjmt97xpjf.1	https://doi.org/10.17632/tjmt97xpjf.1	PROPN
admet-1335	23	9	http://creativecommons.org/licenses/by/4.0/	http://creativecommons.org/licenses/by/4.0/	PROPN
admet-1335	23	10	pallavi	pallavi	PROPN
admet-1335	23	11	and	and	CCONJ
admet-1335	23	12	rakshitha	rakshitha	PROPN
admet-1335	23	13	admet	admet	PROPN
admet-1335	23	14	&	&	CCONJ
admet-1335	23	15	dmpk	dmpk	PROPN
admet-1335	23	16	10(3	10(3	NUM
admet-1335	23	17	)	)	PUNCT
admet-1335	23	18	(	(	PUNCT
admet-1335	23	19	2022	2022	NUM
admet-1335	23	20	)	)	PUNCT
admet-1335	23	21	231	231	NUM
admet-1335	23	22	-	-	SYM
admet-1335	23	23	240	240	NUM
admet-1335	23	24	232	232	NUM
admet-1335	23	25	the	the	DET
admet-1335	23	26	reasons	reason	NOUN
admet-1335	23	27	behind	behind	ADP
admet-1335	23	28	this	this	PRON
admet-1335	23	29	is	be	AUX
admet-1335	23	30	that	that	SCONJ
admet-1335	23	31	nowadays	nowadays	ADV
admet-1335	23	32	,	,	PUNCT
admet-1335	23	33	the	the	DET
admet-1335	23	34	use	use	NOUN
admet-1335	23	35	of	of	ADP
admet-1335	23	36	genetically	genetically	ADV
admet-1335	23	37	modified	modify	VERB
admet-1335	23	38	crops	crop	NOUN
admet-1335	23	39	that	that	PRON
admet-1335	23	40	are	be	AUX
admet-1335	23	41	transgenic	transgenic	NOUN
admet-1335	23	42	food	food	NOUN
admet-1335	23	43	crops	crop	NOUN
admet-1335	23	44	is	be	AUX
admet-1335	23	45	increasing	increase	VERB
admet-1335	23	46	rapidly	rapidly	ADV
admet-1335	23	47	.	.	PUNCT
admet-1335	24	1	thus	thus	ADV
admet-1335	24	2	,	,	PUNCT
admet-1335	24	3	it	it	PRON
admet-1335	24	4	is	be	AUX
admet-1335	24	5	necessary	necessary	ADJ
admet-1335	24	6	to	to	PART
admet-1335	24	7	assess	assess	VERB
admet-1335	24	8	them	they	PRON
admet-1335	24	9	before	before	SCONJ
admet-1335	24	10	they	they	PRON
admet-1335	24	11	are	be	AUX
admet-1335	24	12	introduced	introduce	VERB
admet-1335	24	13	into	into	ADP
admet-1335	24	14	the	the	DET
admet-1335	24	15	food	food	NOUN
admet-1335	24	16	chain	chain	NOUN
admet-1335	24	17	.	.	PUNCT
admet-1335	25	1	allergy	allergy	NOUN
admet-1335	25	2	can	can	AUX
admet-1335	25	3	be	be	AUX
admet-1335	25	4	innate	innate	ADJ
admet-1335	25	5	,	,	PUNCT
admet-1335	25	6	acquired	acquire	VERB
admet-1335	25	7	,	,	PUNCT
admet-1335	25	8	predictable	predictable	ADJ
admet-1335	25	9	,	,	PUNCT
admet-1335	25	10	and	and	CCONJ
admet-1335	25	11	at	at	ADP
admet-1335	25	12	times	time	NOUN
admet-1335	25	13	rapid	rapid	ADJ
admet-1335	25	14	.	.	PUNCT
admet-1335	26	1	allergic	allergic	ADJ
admet-1335	26	2	reactions	reaction	NOUN
admet-1335	26	3	are	be	AUX
admet-1335	26	4	caused	cause	VERB
admet-1335	26	5	by	by	ADP
admet-1335	26	6	an	an	DET
admet-1335	26	7	antibody	antibody	NOUN
admet-1335	26	8	called	call	VERB
admet-1335	26	9	immunoglobulin	immunoglobulin	NOUN
admet-1335	26	10	e	e	PROPN
admet-1335	26	11	(	(	PUNCT
admet-1335	26	12	ige	ige	PROPN
admet-1335	26	13	)	)	PUNCT
admet-1335	26	14	,	,	PUNCT
admet-1335	26	15	which	which	PRON
admet-1335	26	16	causes	cause	VERB
admet-1335	26	17	hyperactivity	hyperactivity	NOUN
admet-1335	26	18	in	in	ADP
admet-1335	26	19	white	white	ADJ
admet-1335	26	20	blood	blood	NOUN
admet-1335	26	21	cells	cell	NOUN
admet-1335	26	22	such	such	ADJ
admet-1335	26	23	as	as	ADP
admet-1335	26	24	mast	mast	NOUN
admet-1335	26	25	cells	cell	NOUN
admet-1335	26	26	and	and	CCONJ
admet-1335	26	27	basophils	basophils	PROPN
admet-1335	26	28	,	,	PUNCT
admet-1335	26	29	resulting	result	VERB
admet-1335	26	30	in	in	ADP
admet-1335	26	31	the	the	DET
admet-1335	26	32	production	production	NOUN
admet-1335	26	33	of	of	ADP
admet-1335	26	34	inflammatory	inflammatory	ADJ
admet-1335	26	35	chemicals	chemical	NOUN
admet-1335	26	36	like	like	ADP
admet-1335	26	37	histamine	histamine	NOUN
admet-1335	26	38	.	.	PUNCT
admet-1335	27	1	apart	apart	ADV
admet-1335	27	2	from	from	ADP
admet-1335	27	3	symptoms	symptom	NOUN
admet-1335	27	4	such	such	ADJ
admet-1335	27	5	as	as	ADP
admet-1335	27	6	uneasiness	uneasiness	NOUN
admet-1335	27	7	,	,	PUNCT
admet-1335	27	8	sneezing	sneeze	VERB
admet-1335	27	9	,	,	PUNCT
admet-1335	27	10	wheezing	wheezing	NOUN
admet-1335	27	11	,	,	PUNCT
admet-1335	27	12	and	and	CCONJ
admet-1335	27	13	swelling	swell	VERB
admet-1335	27	14	,	,	PUNCT
admet-1335	27	15	allergic	allergic	ADJ
admet-1335	27	16	reactions	reaction	NOUN
admet-1335	27	17	can	can	AUX
admet-1335	27	18	also	also	ADV
admet-1335	27	19	lead	lead	VERB
admet-1335	27	20	to	to	ADP
admet-1335	27	21	life	life	NOUN
admet-1335	27	22	-	-	PUNCT
admet-1335	27	23	threatening	threaten	VERB
admet-1335	27	24	situations	situation	NOUN
admet-1335	27	25	.	.	PUNCT
admet-1335	28	1	as	as	ADP
admet-1335	28	2	a	a	DET
admet-1335	28	3	result	result	NOUN
admet-1335	28	4	,	,	PUNCT
admet-1335	28	5	assessing	assess	VERB
admet-1335	28	6	them	they	PRON
admet-1335	28	7	is	be	AUX
admet-1335	28	8	critical	critical	ADJ
admet-1335	28	9	to	to	PART
admet-1335	28	10	protect	protect	VERB
admet-1335	28	11	society	society	NOUN
admet-1335	28	12	's	's	PART
admet-1335	28	13	wellbeing	wellbeing	NOUN
admet-1335	28	14	.	.	PUNCT
admet-1335	29	1	according	accord	VERB
admet-1335	29	2	to	to	ADP
admet-1335	29	3	the	the	DET
admet-1335	29	4	food	food	NOUN
admet-1335	29	5	and	and	CCONJ
admet-1335	29	6	agriculture	agriculture	NOUN
admet-1335	29	7	organization	organization	NOUN
admet-1335	29	8	,	,	PUNCT
admet-1335	29	9	a	a	DET
admet-1335	29	10	protein	protein	NOUN
admet-1335	29	11	is	be	AUX
admet-1335	29	12	a	a	DET
admet-1335	29	13	potential	potential	ADJ
admet-1335	29	14	allergen	allergen	NOUN
admet-1335	29	15	if	if	SCONJ
admet-1335	29	16	it	it	PRON
admet-1335	29	17	has	have	VERB
admet-1335	29	18	a	a	DET
admet-1335	29	19	homology	homology	NOUN
admet-1335	29	20	of	of	ADP
admet-1335	29	21	six	six	NUM
admet-1335	29	22	successive	successive	ADJ
admet-1335	29	23	amino	amino	NOUN
admet-1335	29	24	acids	acid	NOUN
admet-1335	29	25	or	or	CCONJ
admet-1335	29	26	a	a	DET
admet-1335	29	27	sequence	sequence	NOUN
admet-1335	29	28	identity	identity	NOUN
admet-1335	29	29	of	of	ADP
admet-1335	29	30	more	more	ADJ
admet-1335	29	31	than	than	ADP
admet-1335	29	32	35	35	NUM
admet-1335	29	33	percent	percent	NOUN
admet-1335	29	34	[	[	X
admet-1335	29	35	1	1	NUM
admet-1335	29	36	]	]	PUNCT
admet-1335	29	37	.	.	PUNCT
admet-1335	30	1	poms	pom	NOUN
admet-1335	30	2	et	et	PROPN
admet-1335	30	3	al	al	PROPN
admet-1335	30	4	.	.	PROPN
admet-1335	30	5	developed	develop	VERB
admet-1335	30	6	pcr	pcr	PROPN
admet-1335	30	7	(	(	PUNCT
admet-1335	30	8	polymerase	polymerase	NOUN
admet-1335	30	9	chain	chain	NOUN
admet-1335	30	10	reaction	reaction	NOUN
admet-1335	30	11	)	)	PUNCT
admet-1335	30	12	in	in	ADP
admet-1335	30	13	conjunction	conjunction	NOUN
admet-1335	30	14	with	with	ADP
admet-1335	30	15	elisa	elisa	NOUN
admet-1335	30	16	(	(	PUNCT
admet-1335	30	17	enzyme	enzyme	NOUN
admet-1335	30	18	-	-	PUNCT
admet-1335	30	19	linked	link	VERB
admet-1335	30	20	immunosorbent	immunosorbent	NOUN
admet-1335	30	21	assay	assay	NOUN
admet-1335	30	22	)	)	PUNCT
admet-1335	30	23	to	to	PART
admet-1335	30	24	find	find	VERB
admet-1335	30	25	potential	potential	ADJ
admet-1335	30	26	allergens	allergen	NOUN
admet-1335	30	27	in	in	ADP
admet-1335	30	28	foods	food	NOUN
admet-1335	30	29	or	or	CCONJ
admet-1335	30	30	an	an	DET
admet-1335	30	31	indicator	indicator	NOUN
admet-1335	30	32	to	to	PART
admet-1335	30	33	detect	detect	VERB
admet-1335	30	34	the	the	DET
admet-1335	30	35	existence	existence	NOUN
admet-1335	30	36	of	of	ADP
admet-1335	30	37	the	the	DET
admet-1335	30	38	offending	offend	VERB
admet-1335	30	39	foods	food	NOUN
admet-1335	30	40	[	[	X
admet-1335	30	41	2	2	NUM
admet-1335	30	42	]	]	PUNCT
admet-1335	30	43	.	.	PUNCT
admet-1335	31	1	algpred	algpre	VERB
admet-1335	31	2	uses	use	VERB
admet-1335	31	3	meme	meme	NOUN
admet-1335	31	4	/	/	SYM
admet-1335	31	5	mast	mast	NOUN
admet-1335	31	6	motif	motif	NOUN
admet-1335	31	7	search	search	NOUN
admet-1335	31	8	to	to	PART
admet-1335	31	9	predict	predict	VERB
admet-1335	31	10	allergens	allergen	NOUN
admet-1335	31	11	and	and	CCONJ
admet-1335	31	12	svm	svm	VERB
admet-1335	31	13	for	for	ADP
admet-1335	31	14	classification	classification	NOUN
admet-1335	31	15	based	base	VERB
admet-1335	31	16	on	on	ADP
admet-1335	31	17	single	single	ADJ
admet-1335	31	18	and	and	CCONJ
admet-1335	31	19	dipeptide	dipeptide	ADJ
admet-1335	31	20	composition	composition	NOUN
admet-1335	31	21	[	[	X
admet-1335	31	22	3	3	NUM
admet-1335	31	23	]	]	PUNCT
admet-1335	31	24	.	.	PUNCT
admet-1335	32	1	allerhunter	allerhunter	PROPN
admet-1335	32	2	uses	use	VERB
admet-1335	32	3	svm	svm	PROPN
admet-1335	32	4	as	as	SCONJ
admet-1335	32	5	the	the	DET
admet-1335	32	6	classifying	classify	VERB
admet-1335	32	7	method	method	NOUN
admet-1335	32	8	and	and	CCONJ
admet-1335	32	9	an	an	DET
admet-1335	32	10	incremental	incremental	ADJ
admet-1335	32	11	pairwise	pairwise	NOUN
admet-1335	32	12	sequence	sequence	NOUN
admet-1335	32	13	comparison	comparison	NOUN
admet-1335	32	14	indexing	indexing	NOUN
admet-1335	32	15	approach	approach	NOUN
admet-1335	32	16	to	to	PART
admet-1335	32	17	identify	identify	VERB
admet-1335	32	18	probable	probable	ADJ
admet-1335	32	19	allergens	allergen	NOUN
admet-1335	32	20	and	and	CCONJ
admet-1335	32	21	allergic	allergic	ADJ
admet-1335	32	22	cross	cross	NOUN
admet-1335	32	23	-	-	NOUN
admet-1335	32	24	reactivity	reactivity	NOUN
admet-1335	32	25	in	in	ADP
admet-1335	32	26	proteins	protein	NOUN
admet-1335	32	27	.	.	PUNCT
admet-1335	33	1	the	the	DET
admet-1335	33	2	paired	pair	VERB
admet-1335	33	3	vectorization	vectorization	NOUN
admet-1335	33	4	system	system	NOUN
admet-1335	33	5	models	model	VERB
admet-1335	33	6	the	the	DET
admet-1335	33	7	essential	essential	ADJ
admet-1335	33	8	elements	element	NOUN
admet-1335	33	9	of	of	ADP
admet-1335	33	10	allergens	allergen	NOUN
admet-1335	33	11	that	that	PRON
admet-1335	33	12	are	be	AUX
admet-1335	33	13	involved	involve	VERB
admet-1335	33	14	in	in	ADP
admet-1335	33	15	cross	cross	ADJ
admet-1335	33	16	-	-	NOUN
admet-1335	33	17	reactivity	reactivity	NOUN
admet-1335	33	18	[	[	X
admet-1335	33	19	4	4	NUM
admet-1335	33	20	]	]	PUNCT
admet-1335	33	21	.	.	PUNCT
admet-1335	34	1	using	use	VERB
admet-1335	34	2	pseudo	pseudo	NOUN
admet-1335	34	3	-	-	ADJ
admet-1335	34	4	amino	amino	ADJ
admet-1335	34	5	acid	acid	NOUN
admet-1335	34	6	composition	composition	NOUN
admet-1335	34	7	(	(	PUNCT
admet-1335	34	8	pseaac	pseaac	NOUN
admet-1335	34	9	)	)	PUNCT
admet-1335	34	10	and	and	CCONJ
admet-1335	34	11	svm	svm	PROPN
admet-1335	34	12	,	,	PUNCT
admet-1335	34	13	a	a	DET
admet-1335	34	14	new	new	ADJ
admet-1335	34	15	technique	technique	NOUN
admet-1335	34	16	for	for	ADP
admet-1335	34	17	identifying	identify	VERB
admet-1335	34	18	and	and	CCONJ
admet-1335	34	19	predicting	predict	VERB
admet-1335	34	20	allergenic	allergenic	ADJ
admet-1335	34	21	proteins	protein	NOUN
admet-1335	34	22	was	be	AUX
admet-1335	34	23	developed	develop	VERB
admet-1335	34	24	.	.	PUNCT
admet-1335	35	1	it	it	PRON
admet-1335	35	2	looked	look	VERB
admet-1335	35	3	at	at	ADP
admet-1335	35	4	sequence	sequence	NOUN
admet-1335	35	5	vector	vector	NOUN
admet-1335	35	6	representations	representation	NOUN
admet-1335	35	7	derived	derive	VERB
admet-1335	35	8	from	from	ADP
admet-1335	35	9	sequence	sequence	NOUN
admet-1335	35	10	attributes	attribute	NOUN
admet-1335	35	11	.	.	PUNCT
admet-1335	36	1	the	the	DET
admet-1335	36	2	minimum	minimum	ADJ
admet-1335	36	3	reliability	reliability	NOUN
admet-1335	36	4	and	and	CCONJ
admet-1335	36	5	maximal	maximal	ADJ
admet-1335	36	6	significance	significance	NOUN
admet-1335	36	7	feature	feature	NOUN
admet-1335	36	8	selection	selection	NOUN
admet-1335	36	9	approach	approach	NOUN
admet-1335	36	10	were	be	AUX
admet-1335	36	11	used	use	VERB
admet-1335	36	12	to	to	PART
admet-1335	36	13	assess	assess	VERB
admet-1335	36	14	the	the	DET
admet-1335	36	15	impact	impact	NOUN
admet-1335	36	16	and	and	CCONJ
admet-1335	36	17	efficiency	efficiency	NOUN
admet-1335	36	18	of	of	ADP
admet-1335	36	19	each	each	DET
admet-1335	36	20	feature	feature	NOUN
admet-1335	36	21	[	[	X
admet-1335	36	22	5	5	NUM
admet-1335	36	23	]	]	PUNCT
admet-1335	36	24	.	.	PUNCT
admet-1335	37	1	vijaykumar	vijaykumar	PROPN
admet-1335	37	2	et	et	PROPN
admet-1335	37	3	al	al	PROPN
admet-1335	37	4	.	.	PROPN
admet-1335	37	5	developed	develop	VERB
admet-1335	37	6	an	an	DET
admet-1335	37	7	innovative	innovative	ADJ
admet-1335	37	8	fuzzy	fuzzy	ADJ
admet-1335	37	9	rule	rule	NOUN
admet-1335	37	10	-	-	PUNCT
admet-1335	37	11	based	base	VERB
admet-1335	37	12	approach	approach	NOUN
admet-1335	37	13	to	to	PART
admet-1335	37	14	investigate	investigate	VERB
admet-1335	37	15	protein	protein	NOUN
admet-1335	37	16	allergenicity	allergenicity	NOUN
admet-1335	37	17	when	when	SCONJ
admet-1335	37	18	the	the	DET
admet-1335	37	19	similarity	similarity	NOUN
admet-1335	37	20	between	between	ADP
admet-1335	37	21	known	know	VERB
admet-1335	37	22	allergens	allergen	NOUN
admet-1335	37	23	and	and	CCONJ
admet-1335	37	24	non	non	NOUN
admet-1335	37	25	-	-	NOUN
admet-1335	37	26	allergens	allergen	NOUN
admet-1335	37	27	is	be	AUX
admet-1335	37	28	low	low	ADJ
admet-1335	37	29	for	for	ADP
admet-1335	37	30	characterizing	characterize	VERB
admet-1335	37	31	allergens	allergen	NOUN
admet-1335	37	32	.	.	PUNCT
admet-1335	38	1	the	the	DET
admet-1335	38	2	results	result	NOUN
admet-1335	38	3	of	of	ADP
admet-1335	38	4	five	five	NUM
admet-1335	38	5	different	different	ADJ
admet-1335	38	6	modules	module	NOUN
admet-1335	38	7	were	be	AUX
admet-1335	38	8	combined	combine	VERB
admet-1335	38	9	:	:	PUNCT
admet-1335	38	10	computational	computational	ADJ
admet-1335	38	11	classifier	classifier	NOUN
admet-1335	38	12	,	,	PUNCT
admet-1335	38	13	pattern	pattern	NOUN
admet-1335	38	14	analysis	analysis	NOUN
admet-1335	38	15	,	,	PUNCT
admet-1335	38	16	global	global	ADJ
admet-1335	38	17	comparison	comparison	NOUN
admet-1335	38	18	with	with	ADP
admet-1335	38	19	allergens	allergen	NOUN
admet-1335	38	20	,	,	PUNCT
admet-1335	38	21	fao	fao	ADJ
admet-1335	38	22	management	management	NOUN
admet-1335	38	23	framework	framework	NOUN
admet-1335	38	24	,	,	PUNCT
admet-1335	38	25	and	and	CCONJ
admet-1335	38	26	prototype	prototype	NOUN
admet-1335	38	27	approach	approach	NOUN
admet-1335	38	28	[	[	X
admet-1335	38	29	6	6	NUM
admet-1335	38	30	]	]	PUNCT
admet-1335	38	31	.	.	PUNCT
admet-1335	39	1	allertop	allertop	PROPN
admet-1335	39	2	was	be	AUX
admet-1335	39	3	developed	develop	VERB
admet-1335	39	4	as	as	ADP
admet-1335	39	5	an	an	DET
admet-1335	39	6	alignment	alignment	NOUN
admet-1335	39	7	-	-	PUNCT
admet-1335	39	8	free	free	ADJ
admet-1335	39	9	allergen	allergen	NOUN
admet-1335	39	10	prediction	prediction	NOUN
admet-1335	39	11	method	method	NOUN
admet-1335	39	12	.	.	PUNCT
admet-1335	40	1	protein	protein	NOUN
admet-1335	40	2	properties	property	NOUN
admet-1335	40	3	were	be	AUX
admet-1335	40	4	defined	define	VERB
admet-1335	40	5	using	use	VERB
admet-1335	40	6	z	z	NOUN
admet-1335	40	7	-	-	PUNCT
admet-1335	40	8	descriptors	descriptor	NOUN
admet-1335	40	9	.	.	PUNCT
admet-1335	41	1	the	the	DET
admet-1335	41	2	acc	acc	PROPN
admet-1335	41	3	transformation	transformation	NOUN
admet-1335	41	4	was	be	AUX
admet-1335	41	5	used	use	VERB
admet-1335	41	6	to	to	PART
admet-1335	41	7	convert	convert	VERB
admet-1335	41	8	the	the	DET
admet-1335	41	9	variable	variable	ADJ
admet-1335	41	10	-	-	PUNCT
admet-1335	41	11	length	length	NOUN
admet-1335	41	12	strings	string	NOUN
admet-1335	41	13	to	to	PART
admet-1335	41	14	uniformlength	uniformlength	VERB
admet-1335	41	15	strings	string	NOUN
admet-1335	41	16	.	.	PUNCT
admet-1335	42	1	the	the	DET
admet-1335	42	2	knn	knn	PROPN
admet-1335	42	3	(	(	PUNCT
admet-1335	42	4	k	k	X
admet-1335	42	5	-	-	PUNCT
admet-1335	42	6	nearest	near	ADJ
admet-1335	42	7	neighbor	neighbor	NOUN
admet-1335	42	8	)	)	PUNCT
admet-1335	42	9	algorithm	algorithm	NOUN
admet-1335	42	10	was	be	AUX
admet-1335	42	11	applied	apply	VERB
admet-1335	42	12	for	for	ADP
admet-1335	42	13	classification	classification	NOUN
admet-1335	42	14	and	and	CCONJ
admet-1335	42	15	consistently	consistently	ADV
admet-1335	42	16	outperformed	outperform	VERB
admet-1335	42	17	other	other	ADJ
admet-1335	42	18	algorithms	algorithm	NOUN
admet-1335	42	19	[	[	X
admet-1335	42	20	7	7	NUM
admet-1335	42	21	]	]	PUNCT
admet-1335	42	22	.	.	PUNCT
admet-1335	43	1	allergenfpwas	allergenfpwas	AUX
admet-1335	43	2	designed	design	VERB
admet-1335	43	3	for	for	ADP
admet-1335	43	4	distinguishing	distinguish	VERB
admet-1335	43	5	allergens	allergen	NOUN
admet-1335	43	6	and	and	CCONJ
admet-1335	43	7	non	non	NOUN
admet-1335	43	8	-	-	NOUN
admet-1335	43	9	allergens	allergen	NOUN
admet-1335	43	10	,	,	PUNCT
admet-1335	43	11	and	and	CCONJ
admet-1335	43	12	a	a	DET
admet-1335	43	13	sequence	sequence	NOUN
admet-1335	43	14	descriptor	descriptor	NOUN
admet-1335	43	15	-	-	PUNCT
admet-1335	43	16	based	base	VERB
admet-1335	43	17	fingerprint	fingerprint	NOUN
admet-1335	43	18	technology	technology	NOUN
admet-1335	43	19	was	be	AUX
admet-1335	43	20	presented	present	VERB
admet-1335	43	21	.	.	PUNCT
admet-1335	44	1	the	the	DET
admet-1335	44	2	strings	string	NOUN
admet-1335	44	3	of	of	ADP
admet-1335	44	4	varying	vary	VERB
admet-1335	44	5	lengths	length	NOUN
admet-1335	44	6	were	be	AUX
admet-1335	44	7	transformed	transform	VERB
admet-1335	44	8	into	into	ADP
admet-1335	44	9	arrays	array	NOUN
admet-1335	44	10	of	of	ADP
admet-1335	44	11	similar	similar	ADJ
admet-1335	44	12	lengths	length	NOUN
admet-1335	44	13	using	use	VERB
admet-1335	44	14	the	the	DET
admet-1335	44	15	acc	acc	PROPN
admet-1335	44	16	transformation	transformation	NOUN
admet-1335	44	17	.	.	PUNCT
admet-1335	45	1	the	the	DET
admet-1335	45	2	results	result	NOUN
admet-1335	45	3	were	be	AUX
admet-1335	45	4	compared	compare	VERB
admet-1335	45	5	using	use	VERB
admet-1335	45	6	tanimoto	tanimoto	PROPN
admet-1335	45	7	coefficients	coefficient	NOUN
admet-1335	45	8	followed	follow	VERB
admet-1335	45	9	by	by	ADP
admet-1335	45	10	the	the	DET
admet-1335	45	11	transformation	transformation	NOUN
admet-1335	45	12	of	of	ADP
admet-1335	45	13	vectors	vector	NOUN
admet-1335	45	14	to	to	ADP
admet-1335	45	15	binary	binary	ADJ
admet-1335	45	16	fingerprints	fingerprint	NOUN
admet-1335	45	17	[	[	X
admet-1335	45	18	8	8	NUM
admet-1335	45	19	]	]	PUNCT
admet-1335	45	20	.	.	PUNCT
admet-1335	46	1	for	for	ADP
admet-1335	46	2	allergenicity	allergenicity	NOUN
admet-1335	46	3	prediction	prediction	NOUN
admet-1335	46	4	,	,	PUNCT
admet-1335	46	5	dimitrov	dimitrov	PROPN
admet-1335	46	6	et	et	PROPN
admet-1335	46	7	al	al	PROPN
admet-1335	46	8	.	.	PROPN
admet-1335	46	9	developed	develop	VERB
admet-1335	46	10	artificial	artificial	ADJ
admet-1335	46	11	neural	neural	ADJ
admet-1335	46	12	network	network	NOUN
admet-1335	46	13	-	-	PUNCT
admet-1335	46	14	based	base	VERB
admet-1335	46	15	algorithms	algorithm	NOUN
admet-1335	46	16	.	.	PUNCT
admet-1335	47	1	as	as	ADP
admet-1335	47	2	a	a	DET
admet-1335	47	3	final	final	ADJ
admet-1335	47	4	step	step	NOUN
admet-1335	47	5	before	before	ADP
admet-1335	47	6	the	the	DET
admet-1335	47	7	ann	ann	PROPN
admet-1335	47	8	modeling	modeling	NOUN
admet-1335	47	9	,	,	PUNCT
admet-1335	47	10	the	the	DET
admet-1335	47	11	vectors	vector	NOUN
admet-1335	47	12	were	be	AUX
admet-1335	47	13	transformed	transform	VERB
admet-1335	47	14	into	into	ADP
admet-1335	47	15	binary	binary	ADJ
admet-1335	47	16	fingerprints	fingerprint	NOUN
admet-1335	47	17	[	[	X
admet-1335	47	18	9	9	NUM
admet-1335	47	19	]	]	PUNCT
admet-1335	47	20	.	.	PUNCT
admet-1335	48	1	allertop	allertop	VERB
admet-1335	48	2	v2	v2	PROPN
admet-1335	48	3	is	be	AUX
admet-1335	48	4	a	a	DET
admet-1335	48	5	highly	highly	ADV
admet-1335	48	6	accurate	accurate	ADJ
admet-1335	48	7	allergen	allergen	NOUN
admet-1335	48	8	prediction	prediction	NOUN
admet-1335	48	9	model	model	NOUN
admet-1335	48	10	based	base	VERB
admet-1335	48	11	on	on	ADP
admet-1335	48	12	amino	amino	NOUN
admet-1335	48	13	acid	acid	NOUN
admet-1335	48	14	characteristics	characteristic	NOUN
admet-1335	48	15	.	.	PUNCT
admet-1335	49	1	the	the	DET
admet-1335	49	2	acc	acc	PROPN
admet-1335	49	3	procedure	procedure	NOUN
admet-1335	49	4	was	be	AUX
admet-1335	49	5	used	use	VERB
admet-1335	49	6	to	to	PART
admet-1335	49	7	transform	transform	VERB
admet-1335	49	8	variable	variable	ADJ
admet-1335	49	9	-	-	PUNCT
admet-1335	49	10	length	length	NOUN
admet-1335	49	11	strings	string	NOUN
admet-1335	49	12	into	into	ADP
admet-1335	49	13	uniform	uniform	ADJ
admet-1335	49	14	-	-	PUNCT
admet-1335	49	15	length	length	NOUN
admet-1335	49	16	vectors	vector	NOUN
admet-1335	49	17	.	.	PUNCT
admet-1335	50	1	in	in	ADP
admet-1335	50	2	comparison	comparison	NOUN
admet-1335	50	3	to	to	ADP
admet-1335	50	4	other	other	ADJ
admet-1335	50	5	classification	classification	NOUN
admet-1335	50	6	approaches	approach	NOUN
admet-1335	50	7	,	,	PUNCT
admet-1335	50	8	the	the	DET
admet-1335	50	9	knn	knn	PROPN
admet-1335	50	10	algorithm	algorithm	PROPN
admet-1335	50	11	produced	produce	VERB
admet-1335	50	12	a	a	DET
admet-1335	50	13	stable	stable	ADJ
admet-1335	50	14	output	output	NOUN
admet-1335	50	15	graph	graph	NOUN
admet-1335	50	16	[	[	X
admet-1335	50	17	10	10	NUM
admet-1335	50	18	]	]	PUNCT
admet-1335	50	19	.	.	PUNCT
admet-1335	51	1	allerdictor	allerdictor	NOUN
admet-1335	51	2	is	be	AUX
admet-1335	51	3	a	a	DET
admet-1335	51	4	pattern	pattern	NOUN
admet-1335	51	5	-	-	PUNCT
admet-1335	51	6	based	base	VERB
admet-1335	51	7	allergy	allergy	NOUN
admet-1335	51	8	prediction	prediction	NOUN
admet-1335	51	9	software	software	NOUN
admet-1335	51	10	that	that	PRON
admet-1335	51	11	interprets	interpret	VERB
admet-1335	51	12	sequence	sequence	NOUN
admet-1335	51	13	data	datum	NOUN
admet-1335	51	14	as	as	ADP
admet-1335	51	15	a	a	DET
admet-1335	51	16	textual	textual	ADJ
admet-1335	51	17	information	information	NOUN
admet-1335	51	18	and	and	CCONJ
admet-1335	51	19	detects	detect	NOUN
admet-1335	51	20	allergens	allergen	VERB
admet-1335	51	21	through	through	ADP
admet-1335	51	22	text	text	NOUN
admet-1335	51	23	classification	classification	NOUN
admet-1335	51	24	using	use	VERB
admet-1335	51	25	support	support	NOUN
admet-1335	51	26	vector	vector	NOUN
admet-1335	51	27	machines	machine	NOUN
admet-1335	51	28	[	[	X
admet-1335	51	29	11	11	NUM
admet-1335	51	30	]	]	PUNCT
admet-1335	51	31	.	.	PUNCT
admet-1335	52	1	cross	cross	VERB
admet-1335	52	2	-	-	ADJ
admet-1335	52	3	react	react	ADJ
admet-1335	52	4	was	be	AUX
admet-1335	52	5	a	a	DET
admet-1335	52	6	computational	computational	ADJ
admet-1335	52	7	framework	framework	NOUN
admet-1335	52	8	approach	approach	NOUN
admet-1335	52	9	for	for	ADP
admet-1335	52	10	predicting	predict	VERB
admet-1335	52	11	allergenic	allergenic	ADJ
admet-1335	52	12	protein	protein	NOUN
admet-1335	52	13	’s	’s	PART
admet-1335	52	14	cross	cross	NOUN
admet-1335	52	15	-	-	NOUN
admet-1335	52	16	reactivity	reactivity	NOUN
admet-1335	52	17	.	.	PUNCT
admet-1335	53	1	it	it	PRON
admet-1335	53	2	is	be	AUX
admet-1335	53	3	based	base	VERB
admet-1335	53	4	on	on	ADP
admet-1335	53	5	the	the	DET
admet-1335	53	6	hypothesis	hypothesis	NOUN
admet-1335	53	7	that	that	PRON
admet-1335	53	8	surface	surface	NOUN
admet-1335	53	9	regions	region	NOUN
admet-1335	53	10	with	with	ADP
admet-1335	53	11	peptide	peptide	ADJ
admet-1335	53	12	compositions	composition	NOUN
admet-1335	53	13	similar	similar	ADJ
admet-1335	53	14	to	to	ADP
admet-1335	53	15	an	an	DET
admet-1335	53	16	antigen	antigen	NOUN
admet-1335	53	17	in	in	ADP
admet-1335	53	18	a	a	DET
admet-1335	53	19	known	know	VERB
admet-1335	53	20	allergen	allergen	NOUN
admet-1335	53	21	can	can	AUX
admet-1335	53	22	be	be	AUX
admet-1335	53	23	detected	detect	VERB
admet-1335	53	24	on	on	ADP
admet-1335	53	25	three	three	NUM
admet-1335	53	26	-	-	PUNCT
admet-1335	53	27	dimensional	dimensional	ADJ
admet-1335	53	28	structures	structure	NOUN
admet-1335	53	29	of	of	ADP
admet-1335	53	30	probable	probable	ADJ
admet-1335	53	31	allergens	allergen	NOUN
admet-1335	53	32	[	[	X
admet-1335	53	33	12	12	NUM
admet-1335	53	34	]	]	PUNCT
admet-1335	53	35	.	.	PUNCT
admet-1335	54	1	a	a	DET
admet-1335	54	2	study	study	NOUN
admet-1335	54	3	of	of	ADP
admet-1335	54	4	ge	ge	PROPN
admet-1335	54	5	(	(	PUNCT
admet-1335	54	6	genetically	genetically	ADV
admet-1335	54	7	engineered	engineer	VERB
admet-1335	54	8	)	)	PUNCT
admet-1335	54	9	crops	crop	NOUN
admet-1335	54	10	found	find	VERB
admet-1335	54	11	they	they	PRON
admet-1335	54	12	are	be	AUX
admet-1335	54	13	as	as	ADV
admet-1335	54	14	safe	safe	ADJ
admet-1335	54	15	as	as	ADP
admet-1335	54	16	conventional	conventional	ADJ
admet-1335	54	17	food	food	NOUN
admet-1335	54	18	crops	crop	NOUN
admet-1335	54	19	.	.	PUNCT
admet-1335	55	1	screening	screen	VERB
admet-1335	55	2	the	the	DET
admet-1335	55	3	recombinant	recombinant	ADJ
admet-1335	55	4	protein	protein	NOUN
admet-1335	55	5	for	for	ADP
admet-1335	55	6	predicting	predict	VERB
admet-1335	55	7	potential	potential	ADJ
admet-1335	55	8	allergens	allergen	NOUN
admet-1335	55	9	is	be	AUX
admet-1335	55	10	one	one	NUM
admet-1335	55	11	of	of	ADP
admet-1335	55	12	the	the	DET
admet-1335	55	13	assessment	assessment	NOUN
admet-1335	55	14	procedures	procedure	NOUN
admet-1335	55	15	for	for	ADP
admet-1335	55	16	ge	ge	PROPN
admet-1335	55	17	crops	crop	NOUN
admet-1335	55	18	.	.	PUNCT
admet-1335	56	1	it	it	PRON
admet-1335	56	2	implies	imply	VERB
admet-1335	56	3	that	that	SCONJ
admet-1335	56	4	there	there	PRON
admet-1335	56	5	is	be	VERB
admet-1335	56	6	currently	currently	ADV
admet-1335	56	7	no	no	DET
admet-1335	56	8	clear	clear	ADJ
admet-1335	56	9	parameter	parameter	NOUN
admet-1335	56	10	that	that	PRON
admet-1335	56	11	can	can	AUX
admet-1335	56	12	be	be	AUX
admet-1335	56	13	used	use	VERB
admet-1335	56	14	to	to	PART
admet-1335	56	15	anticipate	anticipate	VERB
admet-1335	56	16	the	the	DET
admet-1335	56	17	pathogenicity	pathogenicity	NOUN
admet-1335	56	18	of	of	ADP
admet-1335	56	19	proteins	protein	NOUN
admet-1335	56	20	[	[	X
admet-1335	56	21	13	13	NUM
admet-1335	56	22	]	]	PUNCT
admet-1335	56	23	.	.	PUNCT
admet-1335	57	1	allercatpro	allercatpro	PROPN
admet-1335	57	2	analyses	analyse	VERB
admet-1335	57	3	potential	potential	ADJ
admet-1335	57	4	allergenic	allergenic	ADJ
admet-1335	57	5	protein	protein	NOUN
admet-1335	57	6	based	base	VERB
admet-1335	57	7	on	on	ADP
admet-1335	57	8	the	the	DET
admet-1335	57	9	three	three	NUM
admet-1335	57	10	-	-	PUNCT
admet-1335	57	11	dimensional	dimensional	ADJ
admet-1335	57	12	structural	structural	ADJ
admet-1335	57	13	admet	admet	NOUN
admet-1335	57	14	&	&	CCONJ
admet-1335	57	15	dmpk	dmpk	PROPN
admet-1335	57	16	10(3	10(3	NUM
admet-1335	57	17	)	)	PUNCT
admet-1335	57	18	(	(	PUNCT
admet-1335	57	19	2022	2022	NUM
admet-1335	57	20	)	)	PUNCT
admet-1335	57	21	231	231	NUM
admet-1335	57	22	-	-	SYM
admet-1335	57	23	240	240	NUM
admet-1335	57	24	proall	proall	NOUN
admet-1335	57	25	-	-	PUNCT
admet-1335	57	26	d	d	NOUN
admet-1335	57	27	:	:	PUNCT
admet-1335	57	28	protein	protein	NOUN
admet-1335	57	29	allergen	allergen	NOUN
admet-1335	57	30	detection	detection	NOUN
admet-1335	57	31	doi	doi	NOUN
admet-1335	57	32	:	:	PUNCT
admet-1335	57	33	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	57	34	233	233	NUM
admet-1335	57	35	similarity	similarity	NOUN
admet-1335	57	36	.	.	PUNCT
admet-1335	58	1	shifting	shift	VERB
admet-1335	58	2	between	between	ADP
admet-1335	58	3	sequential	sequential	ADJ
admet-1335	58	4	frame	frame	NOUN
admet-1335	58	5	similarities	similarity	NOUN
admet-1335	58	6	to	to	ADP
admet-1335	58	7	b	b	NOUN
admet-1335	58	8	-	-	PUNCT
admet-1335	58	9	cell	cell	NOUN
admet-1335	58	10	epitope	epitope	NOUN
admet-1335	58	11	-	-	PUNCT
admet-1335	58	12	like	like	ADJ
admet-1335	58	13	3d	3d	PROPN
admet-1335	58	14	surface	surface	NOUN
admet-1335	58	15	similarity	similarity	NOUN
admet-1335	58	16	with	with	ADP
admet-1335	58	17	anticipated	anticipate	VERB
admet-1335	58	18	architectures	architecture	NOUN
admet-1335	58	19	was	be	AUX
admet-1335	58	20	investigated	investigate	VERB
admet-1335	58	21	,	,	PUNCT
admet-1335	58	22	and	and	CCONJ
admet-1335	58	23	so	so	ADV
admet-1335	58	24	an	an	DET
admet-1335	58	25	entropy	entropy	ADV
admet-1335	58	26	-	-	PUNCT
admet-1335	58	27	adjusted	adjust	VERB
admet-1335	58	28	hexamer	hexamer	NOUN
admet-1335	58	29	hit	hit	NOUN
admet-1335	58	30	method	method	NOUN
admet-1335	58	31	was	be	AUX
admet-1335	58	32	also	also	ADV
admet-1335	58	33	investigated	investigate	VERB
admet-1335	58	34	[	[	X
admet-1335	58	35	14	14	NUM
admet-1335	58	36	]	]	PUNCT
admet-1335	58	37	.	.	PUNCT
admet-1335	59	1	pallavi	pallavi	VERB
admet-1335	59	2	et	et	PROPN
admet-1335	59	3	al	al	PROPN
admet-1335	59	4	.	.	PROPN
admet-1335	59	5	used	use	VERB
admet-1335	59	6	computational	computational	ADJ
admet-1335	59	7	analysis	analysis	NOUN
admet-1335	59	8	to	to	PART
admet-1335	59	9	compare	compare	VERB
admet-1335	59	10	three	three	NUM
admet-1335	59	11	medications	medication	NOUN
admet-1335	59	12	and	and	CCONJ
admet-1335	59	13	identified	identify	VERB
admet-1335	59	14	the	the	DET
admet-1335	59	15	impediment	impediment	NOUN
admet-1335	59	16	to	to	ADP
admet-1335	59	17	malignant	malignant	ADJ
admet-1335	59	18	cells	cell	NOUN
admet-1335	59	19	that	that	PRON
admet-1335	59	20	cause	cause	VERB
admet-1335	59	21	skin	skin	NOUN
admet-1335	59	22	cancer	cancer	NOUN
admet-1335	59	23	.	.	PUNCT
admet-1335	60	1	they	they	PRON
admet-1335	60	2	also	also	ADV
admet-1335	60	3	used	use	VERB
admet-1335	60	4	homology	homology	NOUN
admet-1335	60	5	modeling	modeling	NOUN
admet-1335	60	6	to	to	PART
admet-1335	60	7	create	create	VERB
admet-1335	60	8	the	the	DET
admet-1335	60	9	3d	3d	NOUN
admet-1335	60	10	framework	framework	NOUN
admet-1335	60	11	of	of	ADP
admet-1335	60	12	a	a	DET
admet-1335	60	13	braf(v600e	braf(v600e	NOUN
admet-1335	60	14	)	)	PUNCT
admet-1335	60	15	protein	protein	NOUN
admet-1335	60	16	genotype	genotype	NOUN
admet-1335	60	17	,	,	PUNCT
admet-1335	60	18	which	which	PRON
admet-1335	60	19	they	they	PRON
admet-1335	60	20	confirmed	confirm	VERB
admet-1335	60	21	using	use	VERB
admet-1335	60	22	the	the	DET
admet-1335	60	23	ramachandran	ramachandran	PROPN
admet-1335	60	24	plot	plot	NOUN
admet-1335	61	1	[	[	X
admet-1335	61	2	15	15	NUM
admet-1335	61	3	]	]	PUNCT
admet-1335	61	4	.	.	PUNCT
admet-1335	62	1	aller	aller	PROPN
admet-1335	62	2	screener	screener	PROPN
admet-1335	62	3	predicts	predict	VERB
admet-1335	62	4	protein	protein	NOUN
admet-1335	62	5	allergenicity	allergenicity	NOUN
admet-1335	62	6	by	by	ADP
admet-1335	62	7	analyzing	analyze	VERB
admet-1335	62	8	hla	hla	PROPN
admet-1335	62	9	binders	binder	NOUN
admet-1335	62	10	derived	derive	VERB
admet-1335	62	11	from	from	ADP
admet-1335	62	12	recognized	recognize	VERB
admet-1335	62	13	allergens	allergen	NOUN
admet-1335	62	14	.	.	PUNCT
admet-1335	63	1	by	by	ADP
admet-1335	63	2	creating	create	VERB
admet-1335	63	3	binders	binder	NOUN
admet-1335	63	4	to	to	ADP
admet-1335	63	5	hla	hla	PROPN
admet-1335	63	6	class	class	PROPN
admet-1335	63	7	ii	ii	PROPN
admet-1335	63	8	proteins	protein	NOUN
admet-1335	63	9	,	,	PUNCT
admet-1335	63	10	it	it	PRON
admet-1335	63	11	could	could	AUX
admet-1335	63	12	predict	predict	VERB
admet-1335	63	13	whether	whether	SCONJ
admet-1335	63	14	a	a	DET
admet-1335	63	15	given	give	VERB
admet-1335	63	16	substance	substance	NOUN
admet-1335	63	17	is	be	AUX
admet-1335	63	18	safe	safe	ADJ
admet-1335	63	19	to	to	PART
admet-1335	63	20	eat	eat	VERB
admet-1335	63	21	or	or	CCONJ
admet-1335	63	22	drink	drink	VERB
admet-1335	64	1	[	[	X
admet-1335	64	2	16	16	NUM
admet-1335	64	3	]	]	PUNCT
admet-1335	64	4	.	.	PUNCT
admet-1335	65	1	algpred	algpre	VERB
admet-1335	65	2	v	v	ADP
admet-1335	65	3	2.0	2.0	NUM
admet-1335	65	4	provides	provide	VERB
admet-1335	65	5	various	various	ADJ
admet-1335	65	6	options	option	NOUN
admet-1335	65	7	,	,	PUNCT
admet-1335	65	8	including	include	VERB
admet-1335	65	9	searching	search	VERB
admet-1335	65	10	for	for	ADP
admet-1335	65	11	motifs	motif	NOUN
admet-1335	65	12	in	in	ADP
admet-1335	65	13	proteins	protein	NOUN
admet-1335	65	14	found	find	VERB
admet-1335	65	15	by	by	ADP
admet-1335	65	16	meme	meme	NOUN
admet-1335	65	17	/	/	SYM
admet-1335	65	18	mast	mast	NOUN
admet-1335	65	19	and	and	CCONJ
admet-1335	65	20	merci	merci	PROPN
admet-1335	65	21	features	feature	NOUN
admet-1335	65	22	such	such	ADJ
admet-1335	65	23	as	as	ADP
admet-1335	65	24	blast	blast	NOUN
admet-1335	65	25	-	-	PUNCT
admet-1335	65	26	based	base	VERB
admet-1335	65	27	similarity	similarity	NOUN
admet-1335	65	28	searches	search	NOUN
admet-1335	65	29	and	and	CCONJ
admet-1335	65	30	ige	ige	PROPN
admet-1335	65	31	epitope	epitope	PROPN
admet-1335	65	32	mapping	mapping	NOUN
admet-1335	66	1	[	[	X
admet-1335	66	2	17	17	NUM
admet-1335	66	3	]	]	PUNCT
admet-1335	66	4	.	.	PUNCT
admet-1335	67	1	wang	wang	PROPN
admet-1335	67	2	et	et	PROPN
admet-1335	67	3	al	al	PROPN
admet-1335	67	4	.	.	PROPN
admet-1335	67	5	demonstrated	demonstrate	VERB
admet-1335	67	6	the	the	DET
admet-1335	67	7	superiority	superiority	NOUN
admet-1335	67	8	of	of	ADP
admet-1335	67	9	their	their	PRON
admet-1335	67	10	proposed	propose	VERB
admet-1335	67	11	technique	technique	NOUN
admet-1335	67	12	by	by	ADP
admet-1335	67	13	using	use	VERB
admet-1335	67	14	numerous	numerous	ADJ
admet-1335	67	15	supervised	supervised	ADJ
admet-1335	67	16	algorithms	algorithm	NOUN
admet-1335	67	17	as	as	ADP
admet-1335	67	18	baseline	baseline	NOUN
admet-1335	67	19	classifiers	classifier	NOUN
admet-1335	67	20	.	.	PUNCT
admet-1335	68	1	the	the	DET
admet-1335	68	2	greatest	great	ADJ
admet-1335	68	3	auc	auc	NOUN
admet-1335	68	4	value	value	NOUN
admet-1335	68	5	was	be	AUX
admet-1335	68	6	0.9578	0.9578	NUM
admet-1335	68	7	for	for	ADP
admet-1335	68	8	the	the	DET
admet-1335	68	9	deep	deep	ADJ
admet-1335	68	10	learning	learning	NOUN
admet-1335	68	11	model	model	NOUN
admet-1335	68	12	,	,	PUNCT
admet-1335	68	13	which	which	PRON
admet-1335	68	14	was	be	AUX
admet-1335	68	15	superior	superior	ADJ
admet-1335	68	16	to	to	ADP
admet-1335	68	17	the	the	DET
admet-1335	68	18	ensemble	ensemble	ADJ
admet-1335	68	19	learning	learning	NOUN
admet-1335	68	20	and	and	CCONJ
admet-1335	68	21	baseline	baseline	NOUN
admet-1335	68	22	approaches	approach	NOUN
admet-1335	68	23	,	,	PUNCT
admet-1335	68	24	according	accord	VERB
admet-1335	68	25	to	to	ADP
admet-1335	68	26	the	the	DET
admet-1335	68	27	results	result	NOUN
admet-1335	68	28	of	of	ADP
admet-1335	68	29	5	5	NUM
admet-1335	68	30	-	-	ADJ
admet-1335	68	31	fold	fold	ADJ
admet-1335	68	32	cross	cross	NOUN
admet-1335	68	33	-	-	NOUN
admet-1335	68	34	validation	validation	ADJ
admet-1335	68	35	[	[	X
admet-1335	68	36	18	18	NUM
admet-1335	68	37	]	]	PUNCT
admet-1335	68	38	.	.	PUNCT
admet-1335	69	1	this	this	DET
admet-1335	69	2	paper	paper	NOUN
admet-1335	69	3	comprises	comprise	VERB
admet-1335	69	4	the	the	DET
admet-1335	69	5	report	report	NOUN
admet-1335	69	6	on	on	ADP
admet-1335	69	7	the	the	DET
admet-1335	69	8	development	development	NOUN
admet-1335	69	9	methods	method	NOUN
admet-1335	69	10	of	of	ADP
admet-1335	69	11	a	a	DET
admet-1335	69	12	set	set	NOUN
admet-1335	69	13	of	of	ADP
admet-1335	69	14	novel	novel	ADJ
admet-1335	69	15	allergen	allergen	NOUN
admet-1335	69	16	prediction	prediction	NOUN
admet-1335	69	17	models	model	NOUN
admet-1335	69	18	that	that	PRON
admet-1335	69	19	use	use	VERB
admet-1335	69	20	the	the	DET
admet-1335	69	21	knowledge	knowledge	NOUN
admet-1335	69	22	gained	gain	VERB
admet-1335	69	23	via	via	ADP
admet-1335	69	24	a	a	DET
admet-1335	69	25	publicly	publicly	ADV
admet-1335	69	26	available	available	ADJ
admet-1335	69	27	server	server	NOUN
admet-1335	69	28	:	:	PUNCT
admet-1335	69	29	allertop	allertop	NOUN
admet-1335	69	30	v.2	v.2	PROPN
admet-1335	70	1	[	[	X
admet-1335	70	2	10	10	NUM
admet-1335	70	3	]	]	PUNCT
admet-1335	70	4	.	.	PUNCT
admet-1335	71	1	we	we	PRON
admet-1335	71	2	propose	propose	VERB
admet-1335	71	3	the	the	DET
admet-1335	71	4	long	long	ADJ
admet-1335	71	5	shortterm	shortterm	NOUN
admet-1335	71	6	memory	memory	NOUN
admet-1335	71	7	(	(	PUNCT
admet-1335	71	8	lstm	lstm	NOUN
admet-1335	71	9	)	)	PUNCT
admet-1335	71	10	as	as	ADP
admet-1335	71	11	a	a	DET
admet-1335	71	12	rapid	rapid	ADJ
admet-1335	71	13	model	model	NOUN
admet-1335	71	14	-	-	PUNCT
admet-1335	71	15	based	base	VERB
admet-1335	71	16	recurrent	recurrent	ADJ
admet-1335	71	17	neural	neural	ADJ
admet-1335	71	18	network	network	NOUN
admet-1335	71	19	for	for	ADP
admet-1335	71	20	protein	protein	NOUN
admet-1335	71	21	allergen	allergen	NOUN
admet-1335	71	22	detection	detection	NOUN
admet-1335	71	23	.	.	PUNCT
admet-1335	72	1	lstm	lstm	NOUN
admet-1335	72	2	is	be	AUX
admet-1335	72	3	primarily	primarily	ADV
admet-1335	72	4	used	use	VERB
admet-1335	72	5	to	to	PART
admet-1335	72	6	handle	handle	VERB
admet-1335	72	7	long	long	ADJ
admet-1335	72	8	-	-	PUNCT
admet-1335	72	9	term	term	NOUN
admet-1335	72	10	dependence	dependence	NOUN
admet-1335	72	11	problems	problem	NOUN
admet-1335	72	12	and	and	CCONJ
admet-1335	72	13	is	be	AUX
admet-1335	72	14	best	well	ADV
admet-1335	72	15	suited	suit	VERB
admet-1335	72	16	for	for	ADP
admet-1335	72	17	time	time	NOUN
admet-1335	72	18	series	series	NOUN
admet-1335	72	19	or	or	CCONJ
admet-1335	72	20	sequential	sequential	ADJ
admet-1335	72	21	data	datum	NOUN
admet-1335	72	22	.	.	PUNCT
admet-1335	73	1	because	because	SCONJ
admet-1335	73	2	our	our	PRON
admet-1335	73	3	dataset	dataset	NOUN
admet-1335	73	4	,	,	PUNCT
admet-1335	73	5	the	the	DET
admet-1335	73	6	protein	protein	NOUN
admet-1335	73	7	dataset	dataset	NOUN
admet-1335	73	8	,	,	PUNCT
admet-1335	73	9	is	be	AUX
admet-1335	73	10	similarly	similarly	ADV
admet-1335	73	11	in	in	ADP
admet-1335	73	12	sequential	sequential	ADJ
admet-1335	73	13	form	form	NOUN
admet-1335	73	14	,	,	PUNCT
admet-1335	73	15	lstm	lstm	NOUN
admet-1335	73	16	would	would	AUX
admet-1335	73	17	be	be	AUX
admet-1335	73	18	a	a	DET
admet-1335	73	19	better	well	ADJ
admet-1335	73	20	method	method	NOUN
admet-1335	73	21	for	for	ADP
admet-1335	73	22	classification	classification	NOUN
admet-1335	73	23	with	with	ADP
admet-1335	73	24	enhanced	enhanced	ADJ
admet-1335	73	25	performance	performance	NOUN
admet-1335	73	26	.	.	PUNCT
admet-1335	74	1	also	also	ADV
admet-1335	74	2	,	,	PUNCT
admet-1335	74	3	a	a	DET
admet-1335	74	4	few	few	ADJ
admet-1335	74	5	machine	machine	NOUN
admet-1335	74	6	learning	learning	NOUN
admet-1335	74	7	and	and	CCONJ
admet-1335	74	8	ensemble	ensemble	ADJ
admet-1335	74	9	learning	learning	NOUN
admet-1335	74	10	algorithms	algorithm	NOUN
admet-1335	74	11	have	have	AUX
admet-1335	74	12	been	be	AUX
admet-1335	74	13	evaluated	evaluate	VERB
admet-1335	74	14	for	for	ADP
admet-1335	74	15	comparison	comparison	NOUN
admet-1335	74	16	and	and	CCONJ
admet-1335	74	17	classification	classification	NOUN
admet-1335	74	18	purposes	purpose	NOUN
admet-1335	74	19	.	.	PUNCT
admet-1335	75	1	methods	method	NOUN
admet-1335	75	2	protein	protein	NOUN
admet-1335	75	3	data	datum	NOUN
admet-1335	75	4	sets	set	VERB
admet-1335	75	5	we	we	PRON
admet-1335	75	6	gathered	gather	VERB
admet-1335	75	7	a	a	DET
admet-1335	75	8	total	total	NOUN
admet-1335	75	9	of	of	ADP
admet-1335	75	10	2,427	2,427	NUM
admet-1335	75	11	allergens	allergen	NOUN
admet-1335	75	12	and	and	CCONJ
admet-1335	75	13	2,427	2,427	NUM
admet-1335	75	14	non	non	NOUN
admet-1335	75	15	-	-	NOUN
admet-1335	75	16	allergens	allergen	NOUN
admet-1335	75	17	from	from	ADP
admet-1335	75	18	a	a	DET
admet-1335	75	19	variety	variety	NOUN
admet-1335	75	20	of	of	ADP
admet-1335	75	21	sources	source	NOUN
admet-1335	75	22	,	,	PUNCT
admet-1335	75	23	including	include	VERB
admet-1335	75	24	the	the	DET
admet-1335	75	25	central	central	ADJ
admet-1335	75	26	science	science	NOUN
admet-1335	75	27	laboratory	laboratory	NOUN
admet-1335	75	28	and	and	CCONJ
admet-1335	75	29	the	the	DET
admet-1335	75	30	national	national	ADJ
admet-1335	75	31	center	center	NOUN
admet-1335	75	32	for	for	ADP
admet-1335	75	33	biotechnology	biotechnology	NOUN
admet-1335	75	34	information	information	NOUN
admet-1335	75	35	(	(	PUNCT
admet-1335	75	36	ncbi	ncbi	NOUN
admet-1335	75	37	)	)	PUNCT
admet-1335	75	38	.	.	PUNCT
admet-1335	76	1	the	the	DET
admet-1335	76	2	redundancies	redundancy	NOUN
admet-1335	76	3	were	be	AUX
admet-1335	76	4	eliminated	eliminate	VERB
admet-1335	76	5	.	.	PUNCT
admet-1335	77	1	a	a	DET
admet-1335	77	2	sample	sample	NOUN
admet-1335	77	3	protein	protein	NOUN
admet-1335	77	4	sequence	sequence	NOUN
admet-1335	77	5	is	be	AUX
admet-1335	77	6	shown	show	VERB
admet-1335	77	7	in	in	ADP
admet-1335	77	8	figure	figure	NOUN
admet-1335	77	9	1	1	NUM
admet-1335	77	10	.	.	PUNCT
admet-1335	78	1	>	>	PUNCT
admet-1335	78	2	gi	gi	NOUN
admet-1335	78	3	│	│	ADJ
admet-1335	78	4	83715928	83715928	NUM
admet-1335	78	5	│	│	SYM
admet-1335	78	6	dbj	dbj	NOUN
admet-1335	78	7	│	│	NOUN
admet-1335	78	8	bae54429.1	bae54429.1	NUM
admet-1335	78	9	│	│	ADJ
admet-1335	78	10	tropomyosin	tropomyosin	NOUN
admet-1335	79	1	[	[	X
admet-1335	79	2	sepia	sepia	NOUN
admet-1335	79	3	esculenta	esculenta	NOUN
admet-1335	79	4	]	]	PUNCT
admet-1335	80	1	mdaikkkmlamkmekevatdkaeqteqslrdledaknkteedlstlqkkysnlendfdna	mdaikkkmlamkmekevatdkaeqteqslrdledaknkteedlstlqkkysnlendfdna	PROPN
admet-1335	80	2	neqltaantnleasekrvaeceseiqglnrriqlleedlerseerltsaqskledaskaa	neqltaantnleasekrvaeceseiqglnrriqlleedlerseerltsaqskledaskaa	NOUN
admet-1335	80	3	desergrkvlenrsqgdeeridllekqleeakwiaedadrkfdeaarklaitevdlerae	desergrkvlenrsqgdeeridllekqleeakwiaedadrkfdeaarklaitevdlerae	NOUN
admet-1335	80	4	figure	figure	NOUN
admet-1335	80	5	1	1	NUM
admet-1335	80	6	.	.	PUNCT
admet-1335	81	1	sample	sample	NOUN
admet-1335	81	2	dataset	dataset	VERB
admet-1335	81	3	in	in	ADP
admet-1335	81	4	fasta	fasta	PROPN
admet-1335	81	5	format	format	NOUN
admet-1335	81	6	of	of	ADP
admet-1335	81	7	a	a	DET
admet-1335	81	8	protein	protein	NOUN
admet-1335	81	9	sequence	sequence	NOUN
admet-1335	81	10	e	e	NOUN
admet-1335	81	11	-	-	NOUN
admet-1335	81	12	descriptors	descriptor	VERB
admet-1335	81	13	five	five	NUM
admet-1335	81	14	e	e	NOUN
admet-1335	81	15	-	-	NOUN
admet-1335	81	16	descriptors	descriptor	NOUN
admet-1335	81	17	were	be	AUX
admet-1335	81	18	used	use	VERB
admet-1335	81	19	to	to	PART
admet-1335	81	20	characterize	characterize	VERB
admet-1335	81	21	the	the	DET
admet-1335	81	22	protein	protein	NOUN
admet-1335	81	23	sequences	sequence	NOUN
admet-1335	81	24	of	of	ADP
admet-1335	81	25	allergens	allergen	NOUN
admet-1335	81	26	and	and	CCONJ
admet-1335	81	27	non	non	NOUN
admet-1335	81	28	-	-	NOUN
admet-1335	81	29	allergens	allergen	NOUN
admet-1335	81	30	[	[	X
admet-1335	81	31	10	10	NUM
admet-1335	81	32	]	]	PUNCT
admet-1335	81	33	.	.	PUNCT
admet-1335	82	1	venkatarajan	venkatarajan	PROPN
admet-1335	82	2	et	et	PROPN
admet-1335	82	3	al	al	PROPN
admet-1335	82	4	.	.	PROPN
admet-1335	83	1	used	use	VERB
admet-1335	83	2	principal	principal	ADJ
admet-1335	83	3	component	component	NOUN
admet-1335	83	4	analysis	analysis	NOUN
admet-1335	83	5	to	to	PART
admet-1335	83	6	calculate	calculate	VERB
admet-1335	83	7	the	the	DET
admet-1335	83	8	quantitative	quantitative	ADJ
admet-1335	83	9	descriptor	descriptor	NOUN
admet-1335	83	10	values	value	NOUN
admet-1335	83	11	based	base	VERB
admet-1335	83	12	on	on	ADP
admet-1335	83	13	237	237	NUM
admet-1335	83	14	physical	physical	ADJ
admet-1335	83	15	-	-	PUNCT
admet-1335	83	16	chemical	chemical	NOUN
admet-1335	83	17	properties	property	NOUN
admet-1335	83	18	of	of	ADP
admet-1335	83	19	amino	amino	ADJ
admet-1335	83	20	acids	acid	NOUN
admet-1335	83	21	.	.	PUNCT
admet-1335	84	1	pca	pca	NOUN
admet-1335	84	2	of	of	ADP
admet-1335	84	3	amino	amino	NOUN
admet-1335	84	4	acid	acid	NOUN
admet-1335	84	5	properties	property	NOUN
admet-1335	84	6	extracted	extract	VERB
admet-1335	84	7	5	5	NUM
admet-1335	84	8	orthogonal	orthogonal	ADJ
admet-1335	84	9	edescriptors	edescriptor	NOUN
admet-1335	84	10	,	,	PUNCT
admet-1335	84	11	which	which	PRON
admet-1335	84	12	are	be	AUX
admet-1335	84	13	the	the	DET
admet-1335	84	14	eigenvectors	eigenvector	NOUN
admet-1335	84	15	of	of	ADP
admet-1335	84	16	the	the	DET
admet-1335	84	17	covariance	covariance	NOUN
admet-1335	84	18	matrix	matrix	NOUN
admet-1335	84	19	[	[	X
admet-1335	84	20	19	19	NUM
admet-1335	84	21	]	]	PUNCT
admet-1335	84	22	.	.	PUNCT
admet-1335	85	1	we	we	PRON
admet-1335	85	2	have	have	AUX
admet-1335	85	3	considered	consider	VERB
admet-1335	85	4	the	the	DET
admet-1335	85	5	same	same	ADJ
admet-1335	85	6	five	five	NUM
admet-1335	85	7	edescriptors	edescriptor	NOUN
admet-1335	85	8	that	that	PRON
admet-1335	85	9	were	be	AUX
admet-1335	85	10	used	use	VERB
admet-1335	85	11	to	to	PART
admet-1335	85	12	define	define	VERB
admet-1335	85	13	the	the	DET
admet-1335	85	14	characteristics	characteristic	NOUN
admet-1335	85	15	of	of	ADP
admet-1335	85	16	amino	amino	ADJ
admet-1335	85	17	acids	acid	NOUN
admet-1335	86	1	[	[	X
admet-1335	86	2	10	10	NUM
admet-1335	86	3	]	]	PUNCT
admet-1335	86	4	.	.	PUNCT
admet-1335	87	1	e1	e1	NOUN
admet-1335	87	2	denotes	denote	VERB
admet-1335	87	3	the	the	DET
admet-1335	87	4	hydrophilic	hydrophilic	ADJ
admet-1335	87	5	nature	nature	NOUN
admet-1335	87	6	of	of	ADP
admet-1335	87	7	peptides	peptide	NOUN
admet-1335	87	8	,	,	PUNCT
admet-1335	87	9	e2	e2	VERB
admet-1335	87	10	their	their	PRON
admet-1335	87	11	length	length	NOUN
admet-1335	87	12	,	,	PUNCT
admet-1335	87	13	e3	e3	VERB
admet-1335	87	14	their	their	PRON
admet-1335	87	15	tendency	tendency	NOUN
admet-1335	87	16	for	for	ADP
admet-1335	87	17	helical	helical	ADJ
admet-1335	87	18	formation	formation	NOUN
admet-1335	87	19	,	,	PUNCT
admet-1335	87	20	e4	e4	VERB
admet-1335	87	21	their	their	PRON
admet-1335	87	22	abundance	abundance	NOUN
admet-1335	87	23	and	and	CCONJ
admet-1335	87	24	distribution	distribution	NOUN
admet-1335	87	25	,	,	PUNCT
admet-1335	87	26	and	and	CCONJ
admet-1335	87	27	e5	e5	VERB
admet-1335	87	28	their	their	PRON
admet-1335	87	29	tendency	tendency	NOUN
admet-1335	87	30	for	for	ADP
admet-1335	87	31	β	β	X
admet-1335	87	32	strand	strand	NOUN
admet-1335	87	33	formation	formation	NOUN
admet-1335	87	34	.	.	PUNCT
admet-1335	88	1	auto	auto	NOUN
admet-1335	88	2	cross	cross	ADJ
admet-1335	88	3	-	-	ADJ
admet-1335	88	4	covariance	covariance	ADJ
admet-1335	88	5	transformation	transformation	NOUN
admet-1335	88	6	proteins	protein	NOUN
admet-1335	88	7	are	be	AUX
admet-1335	88	8	composed	compose	VERB
admet-1335	88	9	of	of	ADP
admet-1335	88	10	amino	amino	NOUN
admet-1335	88	11	acid	acid	NOUN
admet-1335	88	12	sequences	sequence	NOUN
admet-1335	88	13	,	,	PUNCT
admet-1335	88	14	each	each	DET
admet-1335	88	15	distinct	distinct	ADJ
admet-1335	88	16	and	and	CCONJ
admet-1335	88	17	varies	vary	VERB
admet-1335	88	18	in	in	ADP
admet-1335	88	19	length	length	NOUN
admet-1335	88	20	.	.	PUNCT
admet-1335	89	1	so	so	ADV
admet-1335	89	2	,	,	PUNCT
admet-1335	89	3	acc	acc	PROPN
admet-1335	89	4	transformation	transformation	NOUN
admet-1335	89	5	was	be	AUX
admet-1335	89	6	employed	employ	VERB
admet-1335	89	7	to	to	PART
admet-1335	89	8	convert	convert	VERB
admet-1335	89	9	the	the	DET
admet-1335	89	10	variable	variable	ADJ
admet-1335	89	11	-	-	PUNCT
admet-1335	89	12	length	length	NOUN
admet-1335	89	13	sequence	sequence	NOUN
admet-1335	89	14	to	to	AUX
admet-1335	89	15	uniform	uniform	ADJ
admet-1335	89	16	length	length	NOUN
admet-1335	89	17	so	so	SCONJ
admet-1335	89	18	that	that	SCONJ
admet-1335	89	19	the	the	DET
admet-1335	89	20	classification	classification	NOUN
admet-1335	89	21	algorithms	algorithm	NOUN
admet-1335	89	22	could	could	AUX
admet-1335	89	23	be	be	AUX
admet-1335	89	24	applied	apply	VERB
admet-1335	89	25	to	to	ADP
admet-1335	89	26	it	it	PRON
admet-1335	89	27	.	.	PUNCT
admet-1335	90	1	here	here	ADV
admet-1335	90	2	,	,	PUNCT
admet-1335	90	3	the	the	DET
admet-1335	90	4	5	5	NUM
admet-1335	90	5	e	e	NOUN
admet-1335	90	6	-	-	NOUN
admet-1335	90	7	descriptors	descriptor	NOUN
admet-1335	90	8	have	have	AUX
admet-1335	90	9	been	be	AUX
admet-1335	90	10	considered	consider	VERB
admet-1335	90	11	,	,	PUNCT
admet-1335	90	12	which	which	PRON
admet-1335	90	13	were	be	AUX
admet-1335	90	14	derived	derive	VERB
admet-1335	90	15	from	from	ADP
admet-1335	90	16	237	237	NUM
admet-1335	90	17	physiochemical	physiochemical	ADJ
admet-1335	90	18	properties	property	NOUN
admet-1335	90	19	of	of	ADP
admet-1335	90	20	amino	amino	ADJ
admet-1335	90	21	acids	acid	NOUN
admet-1335	90	22	as	as	SCONJ
admet-1335	90	23	used	use	VERB
admet-1335	90	24	by	by	ADP
admet-1335	90	25	dimitrov	dimitrov	PROPN
admet-1335	90	26	et	et	PROPN
admet-1335	90	27	al	al	PROPN
admet-1335	90	28	.	.	PUNCT
admet-1335	91	1	[	[	X
admet-1335	91	2	10	10	NUM
admet-1335	91	3	]	]	PUNCT
admet-1335	91	4	.	.	PUNCT
admet-1335	92	1	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	92	2	pallavi	pallavi	NOUN
admet-1335	92	3	and	and	CCONJ
admet-1335	92	4	rakshitha	rakshitha	PROPN
admet-1335	92	5	admet	admet	PROPN
admet-1335	92	6	&	&	CCONJ
admet-1335	92	7	dmpk	dmpk	PROPN
admet-1335	92	8	10(3	10(3	NUM
admet-1335	92	9	)	)	PUNCT
admet-1335	92	10	(	(	PUNCT
admet-1335	92	11	2022	2022	NUM
admet-1335	92	12	)	)	PUNCT
admet-1335	92	13	231	231	NUM
admet-1335	92	14	-	-	SYM
admet-1335	92	15	240	240	NUM
admet-1335	92	16	234	234	NUM
admet-1335	92	17	auto	auto	NOUN
admet-1335	92	18	cross	cross	NOUN
admet-1335	92	19	covariance	covariance	NOUN
admet-1335	92	20	includes	include	VERB
admet-1335	92	21	auto	auto	NOUN
admet-1335	92	22	covariance	covariance	NOUN
admet-1335	92	23	and	and	CCONJ
admet-1335	92	24	cross	cross	NOUN
admet-1335	92	25	covariance	covariance	NOUN
admet-1335	92	26	.	.	PUNCT
admet-1335	93	1	the	the	DET
admet-1335	93	2	equation	equation	NOUN
admet-1335	93	3	to	to	PART
admet-1335	93	4	calculate	calculate	VERB
admet-1335	93	5	auto	auto	NOUN
admet-1335	93	6	covariance	covariance	NOUN
admet-1335	93	7	is	be	AUX
admet-1335	93	8	as	as	SCONJ
admet-1335	93	9	follows	follow	VERB
admet-1335	93	10	:	:	PUNCT
admet-1335	93	11	j	j	PROPN
admet-1335	93	12	,	,	PUNCT
admet-1335	93	13	i	i	PROPN
admet-1335	93	14	j	j	PROPN
admet-1335	93	15	,	,	PUNCT
admet-1335	93	16	i+lag	i+lag	NOUN
admet-1335	94	1	jj	jj	NOUN
admet-1335	94	2	i	i	PRON
admet-1335	94	3	(	(	PUNCT
admet-1335	94	4	)	)	PUNCT
admet-1335	94	5	n	n	CCONJ
admet-1335	94	6	lag	lag	NOUN
admet-1335	94	7	e	e	X
admet-1335	94	8	e	e	X
admet-1335	94	9	acc	acc	PROPN
admet-1335	94	10	lag	lag	VERB
admet-1335	94	11	n	n	PRON
admet-1335	94	12	lag	lag	VERB
admet-1335	94	13			NOUN
admet-1335	94	14			PROPN
admet-1335	94	15			NUM
admet-1335	94	16			NOUN
admet-1335	94	17			X
admet-1335	94	18	(	(	PUNCT
admet-1335	94	19	1	1	X
admet-1335	94	20	)	)	PUNCT
admet-1335	94	21	the	the	DET
admet-1335	94	22	equation	equation	NOUN
admet-1335	94	23	to	to	PART
admet-1335	94	24	calculate	calculate	VERB
admet-1335	94	25	cross	cross	NOUN
admet-1335	94	26	covariance	covariance	NOUN
admet-1335	94	27	is	be	AUX
admet-1335	94	28	as	as	SCONJ
admet-1335	94	29	follows	follow	VERB
admet-1335	94	30	:	:	PUNCT
admet-1335	94	31	j	j	PROPN
admet-1335	94	32	,	,	PUNCT
admet-1335	94	33	i	i	PROPN
admet-1335	94	34	k	k	PROPN
admet-1335	94	35	,	,	PUNCT
admet-1335	94	36	i+lag	i+lag	NOUN
admet-1335	95	1	jk	jk	NOUN
admet-1335	95	2	i	i	PRON
admet-1335	95	3	(	(	PUNCT
admet-1335	95	4	)	)	PUNCT
admet-1335	95	5	j	j	PROPN
admet-1335	96	1	k	k	PROPN
admet-1335	96	2	n	n	CCONJ
admet-1335	96	3	lag	lag	VERB
admet-1335	96	4	e	e	PROPN
admet-1335	96	5	e	e	X
admet-1335	96	6	acc	acc	PROPN
admet-1335	96	7	lag	lag	VERB
admet-1335	96	8	n	n	PRON
admet-1335	96	9	lag	lag	X
admet-1335	96	10			VERB
admet-1335	96	11			NUM
admet-1335	96	12			NUM
admet-1335	96	13			NOUN
admet-1335	96	14			X
admet-1335	96	15	(	(	PUNCT
admet-1335	96	16	2	2	NUM
admet-1335	96	17	)	)	PUNCT
admet-1335	96	18	index	index	NOUN
admet-1335	96	19	j	j	PROPN
admet-1335	96	20	was	be	AUX
admet-1335	96	21	used	use	VERB
admet-1335	96	22	for	for	ADP
admet-1335	96	23	the	the	DET
admet-1335	96	24	e	e	NOUN
admet-1335	96	25	-	-	NOUN
admet-1335	96	26	descriptors	descriptor	NOUN
admet-1335	96	27	(	(	PUNCT
admet-1335	96	28	j	j	NOUN
admet-1335	96	29	=	=	SYM
admet-1335	96	30	1	1	NUM
admet-1335	96	31	,	,	PUNCT
admet-1335	96	32	2	2	NUM
admet-1335	96	33	,	,	PUNCT
admet-1335	96	34	3,4,5	3,4,5	NUM
admet-1335	96	35	)	)	PUNCT
admet-1335	96	36	,	,	PUNCT
admet-1335	96	37	n	n	PRON
admet-1335	96	38	is	be	AUX
admet-1335	96	39	the	the	DET
admet-1335	96	40	number	number	NOUN
admet-1335	96	41	of	of	ADP
admet-1335	96	42	amino	amino	ADJ
admet-1335	96	43	acids	acid	NOUN
admet-1335	96	44	in	in	ADP
admet-1335	96	45	a	a	DET
admet-1335	96	46	sequence	sequence	NOUN
admet-1335	96	47	,	,	PUNCT
admet-1335	96	48	the	the	DET
admet-1335	96	49	index	index	NOUN
admet-1335	96	50	i	i	PRON
admet-1335	96	51	is	be	AUX
admet-1335	96	52	the	the	DET
admet-1335	96	53	amino	amino	NOUN
admet-1335	96	54	acid	acid	NOUN
admet-1335	96	55	position	position	NOUN
admet-1335	96	56	(	(	PUNCT
admet-1335	96	57	i	i	NOUN
admet-1335	96	58	=	=	NOUN
admet-1335	96	59	1	1	NUM
admet-1335	96	60	,	,	PUNCT
admet-1335	96	61	2	2	NUM
admet-1335	96	62	,	,	PUNCT
admet-1335	96	63	...	...	PUNCT
admet-1335	96	64	n	n	CCONJ
admet-1335	96	65	)	)	PUNCT
admet-1335	96	66	and	and	CCONJ
admet-1335	96	67	l	l	NOUN
admet-1335	96	68	is	be	AUX
admet-1335	96	69	the	the	DET
admet-1335	96	70	lag	lag	NOUN
admet-1335	96	71	,	,	PUNCT
admet-1335	96	72	length	length	NOUN
admet-1335	96	73	of	of	ADP
admet-1335	96	74	the	the	DET
admet-1335	96	75	minimum	minimum	ADJ
admet-1335	96	76	sequence	sequence	NOUN
admet-1335	96	77	(	(	PUNCT
admet-1335	96	78	l	l	NOUN
admet-1335	96	79	=	=	SYM
admet-1335	96	80	1	1	NUM
admet-1335	96	81	,	,	PUNCT
admet-1335	96	82	2	2	NUM
admet-1335	96	83	,	,	PUNCT
admet-1335	96	84	...	...	PUNCT
admet-1335	96	85	l	l	NOUN
admet-1335	96	86	)	)	PUNCT
admet-1335	96	87	.	.	PUNCT
admet-1335	97	1	in	in	ADP
admet-1335	97	2	order	order	NOUN
admet-1335	97	3	to	to	PART
admet-1335	97	4	investigate	investigate	VERB
admet-1335	97	5	the	the	DET
admet-1335	97	6	influence	influence	NOUN
admet-1335	97	7	of	of	ADP
admet-1335	97	8	close	close	ADJ
admet-1335	97	9	amino	amino	NOUN
admet-1335	97	10	acid	acid	NOUN
admet-1335	97	11	proximity	proximity	NOUN
admet-1335	97	12	on	on	ADP
admet-1335	97	13	protein	protein	NOUN
admet-1335	97	14	allergenicity	allergenicity	NOUN
admet-1335	97	15	,	,	PUNCT
admet-1335	97	16	a	a	DET
admet-1335	97	17	short	short	ADJ
admet-1335	97	18	range	range	NOUN
admet-1335	97	19	of	of	ADP
admet-1335	97	20	lags	lag	NOUN
admet-1335	97	21	(	(	PUNCT
admet-1335	97	22	l	l	NOUN
admet-1335	97	23	=	=	SYM
admet-1335	97	24	1	1	NUM
admet-1335	97	25	,	,	PUNCT
admet-1335	97	26	2	2	NUM
admet-1335	97	27	,	,	PUNCT
admet-1335	97	28	3	3	NUM
admet-1335	97	29	,	,	PUNCT
admet-1335	97	30	4	4	NUM
admet-1335	97	31	,	,	PUNCT
admet-1335	97	32	5	5	NUM
admet-1335	97	33	)	)	PUNCT
admet-1335	97	34	was	be	AUX
admet-1335	97	35	used	use	VERB
admet-1335	97	36	[	[	PUNCT
admet-1335	97	37	20	20	NUM
admet-1335	97	38	]	]	PUNCT
admet-1335	97	39	.	.	PUNCT
admet-1335	98	1	the	the	DET
admet-1335	98	2	classification	classification	NOUN
admet-1335	98	3	methods	method	NOUN
admet-1335	98	4	adopted	adopt	VERB
admet-1335	98	5	in	in	ADP
admet-1335	98	6	this	this	DET
admet-1335	98	7	research	research	NOUN
admet-1335	98	8	for	for	ADP
admet-1335	98	9	classification	classification	NOUN
admet-1335	98	10	,	,	PUNCT
admet-1335	98	11	a	a	DET
admet-1335	98	12	few	few	ADJ
admet-1335	98	13	machine	machine	NOUN
admet-1335	98	14	learning	learning	NOUN
admet-1335	98	15	,	,	PUNCT
admet-1335	98	16	ensemble	ensemble	ADJ
admet-1335	98	17	learning	learning	NOUN
admet-1335	98	18	,	,	PUNCT
admet-1335	98	19	and	and	CCONJ
admet-1335	98	20	deep	deep	ADJ
admet-1335	98	21	learning	learning	NOUN
admet-1335	98	22	algorithms	algorithm	NOUN
admet-1335	98	23	have	have	AUX
admet-1335	98	24	been	be	AUX
admet-1335	98	25	considered	consider	VERB
admet-1335	98	26	,	,	PUNCT
admet-1335	98	27	which	which	PRON
admet-1335	98	28	include	include	VERB
admet-1335	98	29	:	:	PUNCT
admet-1335	98	30	the	the	DET
admet-1335	98	31	gaussian	gaussian	ADJ
admet-1335	98	32	naive	naive	ADJ
admet-1335	98	33	bayes	bayes	NOUN
admet-1335	98	34	,	,	PUNCT
admet-1335	98	35	radius	radius	NOUN
admet-1335	98	36	neighbour	neighbour	NOUN
admet-1335	98	37	's	's	PART
admet-1335	98	38	classifier	classifier	NOUN
admet-1335	98	39	,	,	PUNCT
admet-1335	98	40	bagging	bagging	NOUN
admet-1335	98	41	classifier	classifier	NOUN
admet-1335	98	42	,	,	PUNCT
admet-1335	98	43	ada	ada	PROPN
admet-1335	98	44	boost	boost	PROPN
admet-1335	98	45	,	,	PUNCT
admet-1335	98	46	linear	linear	ADJ
admet-1335	98	47	discriminant	discriminant	ADJ
admet-1335	98	48	analysis	analysis	NOUN
admet-1335	98	49	,	,	PUNCT
admet-1335	98	50	quadratic	quadratic	ADJ
admet-1335	98	51	discriminant	discriminant	ADJ
admet-1335	98	52	analysis	analysis	NOUN
admet-1335	98	53	,	,	PUNCT
admet-1335	98	54	extra	extra	ADJ
admet-1335	98	55	tree	tree	NOUN
admet-1335	98	56	classifier	classifier	NOUN
admet-1335	98	57	,	,	PUNCT
admet-1335	98	58	and	and	CCONJ
admet-1335	98	59	lstm	lstm	PROPN
admet-1335	98	60	,	,	PUNCT
admet-1335	98	61	which	which	PRON
admet-1335	98	62	have	have	AUX
admet-1335	98	63	been	be	AUX
admet-1335	98	64	implemented	implement	VERB
admet-1335	98	65	in	in	ADP
admet-1335	98	66	python	python	PROPN
admet-1335	98	67	.	.	PUNCT
admet-1335	99	1	hochreiter	hochreiter	PROPN
admet-1335	99	2	and	and	CCONJ
admet-1335	99	3	schmidhuber	schmidhuber	PROPN
admet-1335	99	4	proposed	propose	VERB
admet-1335	99	5	the	the	DET
admet-1335	99	6	term	term	NOUN
admet-1335	99	7	lstm	lstm	NOUN
admet-1335	99	8	(	(	PUNCT
admet-1335	99	9	long	long	ADJ
admet-1335	99	10	short	short	ADJ
admet-1335	99	11	-	-	PUNCT
admet-1335	99	12	term	term	NOUN
admet-1335	99	13	memory	memory	NOUN
admet-1335	99	14	)	)	PUNCT
admet-1335	99	15	in	in	ADP
admet-1335	99	16	1997	1997	NUM
admet-1335	99	17	.	.	PUNCT
admet-1335	100	1	lstms	lstms	PROPN
admet-1335	100	2	are	be	AUX
admet-1335	100	3	a	a	DET
admet-1335	100	4	kind	kind	NOUN
admet-1335	100	5	of	of	ADP
admet-1335	100	6	rnn	rnn	NOUN
admet-1335	100	7	(	(	PUNCT
admet-1335	100	8	recurrent	recurrent	ADJ
admet-1335	100	9	neural	neural	ADJ
admet-1335	100	10	networks	network	NOUN
admet-1335	100	11	)	)	PUNCT
admet-1335	100	12	that	that	PRON
admet-1335	100	13	aid	aid	NOUN
admet-1335	100	14	in	in	ADP
admet-1335	100	15	the	the	DET
admet-1335	100	16	resolution	resolution	NOUN
admet-1335	100	17	of	of	ADP
admet-1335	100	18	the	the	DET
admet-1335	100	19	long	long	ADJ
admet-1335	100	20	-	-	PUNCT
admet-1335	100	21	term	term	NOUN
admet-1335	100	22	dependence	dependence	NOUN
admet-1335	100	23	problem	problem	NOUN
admet-1335	100	24	.	.	PUNCT
admet-1335	101	1	a	a	DET
admet-1335	101	2	conventional	conventional	ADJ
admet-1335	101	3	rnn	rnn	NOUN
admet-1335	101	4	encounters	encounter	VERB
admet-1335	101	5	the	the	DET
admet-1335	101	6	difficulty	difficulty	NOUN
admet-1335	101	7	of	of	ADP
admet-1335	101	8	vanishing	vanish	VERB
admet-1335	101	9	gradient	gradient	NOUN
admet-1335	101	10	problems	problem	NOUN
admet-1335	101	11	,	,	PUNCT
admet-1335	101	12	which	which	PRON
admet-1335	101	13	makes	make	VERB
admet-1335	101	14	learning	learn	VERB
admet-1335	101	15	extended	extended	ADJ
admet-1335	101	16	sequences	sequence	NOUN
admet-1335	101	17	difficult	difficult	ADJ
admet-1335	101	18	.	.	PUNCT
admet-1335	102	1	this	this	PRON
admet-1335	102	2	is	be	AUX
admet-1335	102	3	where	where	SCONJ
admet-1335	102	4	lstm	lstm	NOUN
admet-1335	102	5	comes	come	VERB
admet-1335	102	6	in	in	ADP
admet-1335	102	7	to	to	PART
admet-1335	102	8	address	address	VERB
admet-1335	102	9	the	the	DET
admet-1335	102	10	challenge	challenge	NOUN
admet-1335	102	11	described	describe	VERB
admet-1335	102	12	above	above	ADV
admet-1335	102	13	.	.	PUNCT
admet-1335	103	1	the	the	DET
admet-1335	103	2	lstm	lstm	PROPN
admet-1335	103	3	model	model	NOUN
admet-1335	103	4	is	be	AUX
admet-1335	103	5	built	build	VERB
admet-1335	103	6	iteratively	iteratively	ADV
admet-1335	103	7	.	.	PUNCT
admet-1335	104	1	to	to	PART
admet-1335	104	2	construct	construct	VERB
admet-1335	104	3	the	the	DET
admet-1335	104	4	model	model	NOUN
admet-1335	104	5	,	,	PUNCT
admet-1335	104	6	one	one	PRON
admet-1335	104	7	must	must	AUX
admet-1335	104	8	add	add	VERB
admet-1335	104	9	different	different	ADJ
admet-1335	104	10	sorts	sort	NOUN
admet-1335	104	11	of	of	ADP
admet-1335	104	12	layers	layer	NOUN
admet-1335	104	13	with	with	ADP
admet-1335	104	14	varied	varied	ADJ
admet-1335	104	15	parameters	parameter	NOUN
admet-1335	104	16	and	and	CCONJ
admet-1335	104	17	experiment	experiment	NOUN
admet-1335	104	18	with	with	ADP
admet-1335	104	19	dropout	dropout	NOUN
admet-1335	104	20	layers	layer	NOUN
admet-1335	104	21	.	.	PUNCT
admet-1335	105	1	the	the	DET
admet-1335	105	2	network	network	NOUN
admet-1335	105	3	constructed	construct	VERB
admet-1335	105	4	here	here	ADV
admet-1335	105	5	consists	consist	VERB
admet-1335	105	6	of	of	ADP
admet-1335	105	7	four	four	NUM
admet-1335	105	8	layers	layer	NOUN
admet-1335	105	9	with	with	ADP
admet-1335	105	10	three	three	NUM
admet-1335	105	11	relu	relu	NOUN
admet-1335	105	12	activation	activation	NOUN
admet-1335	105	13	functions	function	NOUN
admet-1335	105	14	and	and	CCONJ
admet-1335	105	15	one	one	NUM
admet-1335	105	16	softmax	softmax	NOUN
admet-1335	105	17	function	function	NOUN
admet-1335	105	18	.	.	PUNCT
admet-1335	106	1	"	"	PUNCT
admet-1335	106	2	categorical	categorical	ADJ
admet-1335	106	3	cross	cross	NOUN
admet-1335	106	4	-	-	NOUN
admet-1335	106	5	entropy	entropy	NOUN
admet-1335	106	6	,	,	PUNCT
admet-1335	106	7	"	"	PUNCT
admet-1335	106	8	was	be	AUX
admet-1335	106	9	considered	consider	VERB
admet-1335	106	10	as	as	ADP
admet-1335	106	11	the	the	DET
admet-1335	106	12	loss	loss	NOUN
admet-1335	106	13	function	function	NOUN
admet-1335	106	14	with	with	ADP
admet-1335	106	15	"	"	PUNCT
admet-1335	106	16	rmsprop	rmsprop	NOUN
admet-1335	106	17	"	"	PUNCT
admet-1335	106	18	as	as	ADP
admet-1335	106	19	the	the	DET
admet-1335	106	20	optimizer	optimizer	NOUN
admet-1335	106	21	.	.	PUNCT
admet-1335	107	1	evaluation	evaluation	NOUN
admet-1335	107	2	of	of	ADP
admet-1335	107	3	performance	performance	NOUN
admet-1335	107	4	for	for	ADP
admet-1335	107	5	training	training	NOUN
admet-1335	107	6	and	and	CCONJ
admet-1335	107	7	testing	testing	NOUN
admet-1335	107	8	purposes	purpose	NOUN
admet-1335	107	9	,	,	PUNCT
admet-1335	107	10	the	the	DET
admet-1335	107	11	data	datum	NOUN
admet-1335	107	12	was	be	AUX
admet-1335	107	13	split	split	VERB
admet-1335	107	14	in	in	ADP
admet-1335	107	15	the	the	DET
admet-1335	107	16	ratio	ratio	NOUN
admet-1335	107	17	80:20	80:20	NUM
admet-1335	107	18	.	.	PUNCT
admet-1335	108	1	the	the	DET
admet-1335	108	2	accuracy	accuracy	NOUN
admet-1335	108	3	results	result	NOUN
admet-1335	108	4	of	of	ADP
admet-1335	108	5	the	the	DET
admet-1335	108	6	model	model	NOUN
admet-1335	108	7	based	base	VERB
admet-1335	108	8	on	on	ADP
admet-1335	108	9	training	training	NOUN
admet-1335	108	10	and	and	CCONJ
admet-1335	108	11	testing	testing	NOUN
admet-1335	108	12	data	datum	NOUN
admet-1335	108	13	has	have	AUX
admet-1335	108	14	been	be	AUX
admet-1335	108	15	represented	represent	VERB
admet-1335	108	16	in	in	ADP
admet-1335	108	17	table	table	NOUN
admet-1335	108	18	2	2	NUM
admet-1335	108	19	.	.	PUNCT
admet-1335	108	20	true	true	ADJ
admet-1335	108	21	positives	positive	NOUN
admet-1335	108	22	(	(	PUNCT
admet-1335	108	23	tp	tp	NOUN
admet-1335	108	24	)	)	PUNCT
admet-1335	108	25	and	and	CCONJ
admet-1335	108	26	true	true	ADJ
admet-1335	108	27	negatives	negative	NOUN
admet-1335	108	28	(	(	PUNCT
admet-1335	108	29	tn	tn	NOUN
admet-1335	108	30	)	)	PUNCT
admet-1335	108	31	were	be	AUX
admet-1335	108	32	assigned	assign	VERB
admet-1335	108	33	to	to	ADP
admet-1335	108	34	the	the	DET
admet-1335	108	35	allergens	allergen	NOUN
admet-1335	108	36	and	and	CCONJ
admet-1335	108	37	non	non	NOUN
admet-1335	108	38	-	-	NOUN
admet-1335	108	39	allergens	allergen	NOUN
admet-1335	108	40	that	that	PRON
admet-1335	108	41	were	be	AUX
admet-1335	108	42	accurately	accurately	ADV
admet-1335	108	43	predicted	predict	VERB
admet-1335	108	44	.	.	PUNCT
admet-1335	109	1	false	false	ADJ
admet-1335	109	2	negatives	negative	NOUN
admet-1335	109	3	(	(	PUNCT
admet-1335	109	4	fn	fn	NOUN
admet-1335	109	5	)	)	PUNCT
admet-1335	109	6	and	and	CCONJ
admet-1335	109	7	false	false	ADJ
admet-1335	109	8	positives	positive	NOUN
admet-1335	109	9	(	(	PUNCT
admet-1335	109	10	fp	fp	X
admet-1335	109	11	)	)	PUNCT
admet-1335	109	12	were	be	AUX
admet-1335	109	13	assigned	assign	VERB
admet-1335	109	14	to	to	ADP
admet-1335	109	15	the	the	DET
admet-1335	109	16	allergen	allergen	NOUN
admet-1335	109	17	and	and	CCONJ
admet-1335	109	18	non	non	ADJ
admet-1335	109	19	-	-	ADJ
admet-1335	109	20	allergen	allergen	NOUN
admet-1335	109	21	identified	identify	VERB
admet-1335	109	22	inaccurately	inaccurately	ADV
admet-1335	109	23	.	.	PUNCT
admet-1335	110	1	precision	precision	NOUN
admet-1335	111	1	[	[	X
admet-1335	111	2	(	(	PUNCT
admet-1335	111	3	tp	tp	NOUN
admet-1335	111	4	)	)	PUNCT
admet-1335	111	5	/(tp	/(tp	PUNCT
admet-1335	112	1	+	+	CCONJ
admet-1335	112	2	fp	fp	X
admet-1335	112	3	)	)	PUNCT
admet-1335	112	4	]	]	PUNCT
admet-1335	112	5	is	be	AUX
admet-1335	112	6	the	the	DET
admet-1335	112	7	fraction	fraction	NOUN
admet-1335	112	8	of	of	ADP
admet-1335	112	9	correctly	correctly	ADV
admet-1335	112	10	predicted	predict	VERB
admet-1335	112	11	samples	sample	NOUN
admet-1335	112	12	among	among	ADP
admet-1335	112	13	the	the	DET
admet-1335	112	14	retrieved	retrieve	VERB
admet-1335	112	15	instances	instance	NOUN
admet-1335	112	16	.	.	PUNCT
admet-1335	113	1	the	the	DET
admet-1335	113	2	recall	recall	NOUN
admet-1335	113	3	[	[	X
admet-1335	113	4	(	(	PUNCT
admet-1335	113	5	tp)/(tp	tp)/(tp	NOUN
admet-1335	113	6	+	+	CCONJ
admet-1335	113	7	fn	fn	NOUN
admet-1335	113	8	)	)	PUNCT
admet-1335	113	9	]	]	PUNCT
admet-1335	113	10	is	be	AUX
admet-1335	113	11	the	the	DET
admet-1335	113	12	ratio	ratio	NOUN
admet-1335	113	13	of	of	ADP
admet-1335	113	14	accurately	accurately	ADV
admet-1335	113	15	identified	identify	VERB
admet-1335	113	16	true	true	ADJ
admet-1335	113	17	positives	positive	NOUN
admet-1335	113	18	to	to	PART
admet-1335	113	19	total	total	VERB
admet-1335	113	20	actual	actual	ADJ
admet-1335	113	21	true	true	ADJ
admet-1335	113	22	positives	positive	NOUN
admet-1335	113	23	.	.	PUNCT
admet-1335	114	1	and	and	CCONJ
admet-1335	114	2	the	the	DET
admet-1335	114	3	f1	f1	PROPN
admet-1335	114	4	score	score	NOUN
admet-1335	114	5	is	be	AUX
admet-1335	114	6	computed	compute	VERB
admet-1335	114	7	as	as	ADP
admet-1335	114	8	[	[	X
admet-1335	114	9	(	(	PUNCT
admet-1335	114	10	2	2	NUM
admet-1335	114	11	*	*	PUNCT
admet-1335	114	12	(	(	PUNCT
admet-1335	114	13	accuracy	accuracy	NOUN
admet-1335	114	14	*	*	PUNCT
admet-1335	114	15	recall)/(precision	recall)/(precision	NOUN
admet-1335	114	16	+	+	CCONJ
admet-1335	114	17	recall	recall	NOUN
admet-1335	114	18	)	)	PUNCT
admet-1335	114	19	]	]	PUNCT
admet-1335	114	20	.	.	PUNCT
admet-1335	115	1	web	web	NOUN
admet-1335	115	2	server	server	NOUN
admet-1335	115	3	for	for	ADP
admet-1335	115	4	allergenicity	allergenicity	NOUN
admet-1335	115	5	prediction	prediction	NOUN
admet-1335	115	6	a	a	DET
admet-1335	115	7	web	web	NOUN
admet-1335	115	8	server	server	NOUN
admet-1335	115	9	,	,	PUNCT
admet-1335	115	10	namely	namely	ADV
admet-1335	115	11	proall	proall	NOUN
admet-1335	115	12	-	-	PUNCT
admet-1335	115	13	d	d	PROPN
admet-1335	115	14	,	,	PUNCT
admet-1335	115	15	has	have	AUX
admet-1335	115	16	been	be	AUX
admet-1335	115	17	developed	develop	VERB
admet-1335	115	18	to	to	PART
admet-1335	115	19	predict	predict	VERB
admet-1335	115	20	the	the	DET
admet-1335	115	21	potential	potential	ADJ
admet-1335	115	22	allergens	allergen	NOUN
admet-1335	115	23	using	use	VERB
admet-1335	115	24	the	the	DET
admet-1335	115	25	lstm	lstm	ADJ
admet-1335	115	26	algorithm	algorithm	NOUN
admet-1335	115	27	.	.	PUNCT
admet-1335	116	1	it	it	PRON
admet-1335	116	2	is	be	AUX
admet-1335	116	3	developed	develop	VERB
admet-1335	116	4	using	use	VERB
admet-1335	116	5	the	the	DET
admet-1335	116	6	python	python	NOUN
admet-1335	116	7	django	django	NOUN
admet-1335	116	8	framework	framework	NOUN
admet-1335	116	9	,	,	PUNCT
admet-1335	116	10	which	which	PRON
admet-1335	116	11	is	be	AUX
admet-1335	116	12	fast	fast	ADJ
admet-1335	116	13	and	and	CCONJ
admet-1335	116	14	user	user	NOUN
admet-1335	116	15	-	-	PUNCT
admet-1335	116	16	friendly	friendly	ADJ
admet-1335	116	17	.	.	PUNCT
admet-1335	117	1	the	the	DET
admet-1335	117	2	detailed	detailed	ADJ
admet-1335	117	3	functioning	functioning	NOUN
admet-1335	117	4	of	of	ADP
admet-1335	117	5	the	the	DET
admet-1335	117	6	webserver	webserver	NOUN
admet-1335	117	7	has	have	AUX
admet-1335	117	8	been	be	AUX
admet-1335	117	9	described	describe	VERB
admet-1335	117	10	in	in	ADP
admet-1335	117	11	the	the	DET
admet-1335	117	12	supplementary	supplementary	ADJ
admet-1335	117	13	section	section	NOUN
admet-1335	117	14	.	.	PUNCT
admet-1335	118	1	results	result	NOUN
admet-1335	118	2	and	and	CCONJ
admet-1335	118	3	discussion	discussion	NOUN
admet-1335	118	4	acc	acc	PROPN
admet-1335	118	5	includes	include	VERB
admet-1335	118	6	both	both	PRON
admet-1335	118	7	autocovariance	autocovariance	NOUN
admet-1335	118	8	and	and	CCONJ
admet-1335	118	9	cross	cross	NOUN
admet-1335	118	10	-	-	NOUN
admet-1335	118	11	covariance	covariance	NOUN
admet-1335	118	12	.	.	PUNCT
admet-1335	119	1	auto	auto	NOUN
admet-1335	119	2	covariance	covariance	NOUN
admet-1335	119	3	is	be	AUX
admet-1335	119	4	calculated	calculate	VERB
admet-1335	119	5	between	between	ADP
admet-1335	119	6	the	the	DET
admet-1335	119	7	same	same	ADJ
admet-1335	119	8	e	e	NOUN
admet-1335	119	9	descriptors	descriptor	NOUN
admet-1335	119	10	,	,	PUNCT
admet-1335	119	11	that	that	PRON
admet-1335	119	12	is	be	AUX
admet-1335	119	13	between	between	ADP
admet-1335	119	14	e1	e1	PROPN
admet-1335	119	15	and	and	CCONJ
admet-1335	119	16	e1	e1	NOUN
admet-1335	119	17	,	,	PUNCT
admet-1335	119	18	along	along	ADP
admet-1335	119	19	with	with	ADP
admet-1335	119	20	the	the	DET
admet-1335	119	21	lag	lag	NOUN
admet-1335	119	22	value	value	NOUN
admet-1335	119	23	.	.	PUNCT
admet-1335	120	1	ac111	ac111	PROPN
admet-1335	120	2	represents	represent	VERB
admet-1335	120	3	the	the	DET
admet-1335	120	4	autocovariance	autocovariance	NOUN
admet-1335	120	5	admet	admet	NOUN
admet-1335	120	6	&	&	CCONJ
admet-1335	120	7	dmpk	dmpk	PROPN
admet-1335	120	8	10(3	10(3	NUM
admet-1335	120	9	)	)	PUNCT
admet-1335	120	10	(	(	PUNCT
admet-1335	120	11	2022	2022	NUM
admet-1335	120	12	)	)	PUNCT
admet-1335	120	13	231	231	NUM
admet-1335	120	14	-	-	SYM
admet-1335	120	15	240	240	NUM
admet-1335	120	16	proall	proall	NOUN
admet-1335	120	17	-	-	PUNCT
admet-1335	120	18	d	d	NOUN
admet-1335	120	19	:	:	PUNCT
admet-1335	120	20	protein	protein	NOUN
admet-1335	120	21	allergen	allergen	NOUN
admet-1335	120	22	detection	detection	NOUN
admet-1335	120	23	doi	doi	NOUN
admet-1335	120	24	:	:	PUNCT
admet-1335	120	25	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	120	26	235	235	NUM
admet-1335	120	27	between	between	ADP
admet-1335	120	28	e1	e1	NOUN
admet-1335	120	29	and	and	CCONJ
admet-1335	120	30	e1	e1	NOUN
admet-1335	120	31	along	along	ADV
admet-1335	120	32	with	with	ADP
admet-1335	120	33	the	the	DET
admet-1335	120	34	lag	lag	NOUN
admet-1335	120	35	value	value	NOUN
admet-1335	120	36	as	as	SCONJ
admet-1335	120	37	shown	show	VERB
admet-1335	120	38	in	in	ADP
admet-1335	120	39	figure	figure	NOUN
admet-1335	120	40	2	2	NUM
admet-1335	120	41	.	.	PUNCT
admet-1335	120	42	cross	cross	NOUN
admet-1335	120	43	covariance	covariance	PROPN
admet-1335	120	44	is	be	AUX
admet-1335	120	45	calculated	calculate	VERB
admet-1335	120	46	between	between	ADP
admet-1335	120	47	the	the	DET
admet-1335	120	48	different	different	ADJ
admet-1335	120	49	e	e	NOUN
admet-1335	120	50	descriptor	descriptor	NOUN
admet-1335	120	51	values	value	NOUN
admet-1335	120	52	,	,	PUNCT
admet-1335	120	53	like	like	INTJ
admet-1335	120	54	between	between	ADP
admet-1335	120	55	e1	e1	PROPN
admet-1335	120	56	and	and	CCONJ
admet-1335	120	57	e2	e2	PROPN
admet-1335	120	58	,	,	PUNCT
admet-1335	120	59	along	along	ADP
admet-1335	120	60	with	with	ADP
admet-1335	120	61	the	the	DET
admet-1335	120	62	lag	lag	NOUN
admet-1335	120	63	value	value	NOUN
admet-1335	120	64	.	.	PUNCT
admet-1335	121	1	the	the	DET
admet-1335	121	2	cross	cross	ADJ
admet-1335	121	3	-	-	ADJ
admet-1335	121	4	covariance	covariance	ADJ
admet-1335	121	5	values	value	NOUN
admet-1335	121	6	will	will	AUX
admet-1335	121	7	be	be	AUX
admet-1335	121	8	represented	represent	VERB
admet-1335	121	9	as	as	ADP
admet-1335	121	10	ac121	ac121	PROPN
admet-1335	121	11	,	,	PUNCT
admet-1335	121	12	ac131	ac131	PROPN
admet-1335	121	13	,	,	PUNCT
admet-1335	121	14	ac145	ac145	PROPN
admet-1335	121	15	,	,	PUNCT
admet-1335	121	16	and	and	CCONJ
admet-1335	121	17	ac431	ac431	PROPN
admet-1335	121	18	.	.	PUNCT
admet-1335	122	1	the	the	DET
admet-1335	122	2	details	detail	NOUN
admet-1335	122	3	of	of	ADP
admet-1335	122	4	acc	acc	PROPN
admet-1335	122	5	implementation	implementation	NOUN
admet-1335	122	6	have	have	AUX
admet-1335	122	7	been	be	AUX
admet-1335	122	8	specified	specify	VERB
admet-1335	122	9	in	in	ADP
admet-1335	122	10	the	the	DET
admet-1335	122	11	supplementary	supplementary	ADJ
admet-1335	122	12	data	datum	NOUN
admet-1335	122	13	.	.	PUNCT
admet-1335	123	1	figure	figure	NOUN
admet-1335	123	2	2	2	NUM
admet-1335	123	3	.	.	PUNCT
admet-1335	124	1	output	output	NOUN
admet-1335	124	2	of	of	ADP
admet-1335	124	3	acc	acc	PROPN
admet-1335	124	4	transformation	transformation	NOUN
admet-1335	124	5	the	the	DET
admet-1335	124	6	classification	classification	NOUN
admet-1335	124	7	methods	method	NOUN
admet-1335	124	8	considered	consider	VERB
admet-1335	124	9	in	in	ADP
admet-1335	124	10	this	this	DET
admet-1335	124	11	research	research	NOUN
admet-1335	124	12	are	be	AUX
admet-1335	124	13	:	:	PUNCT
admet-1335	124	14	the	the	DET
admet-1335	124	15	gaussian	gaussian	ADJ
admet-1335	124	16	naive	naive	ADJ
admet-1335	124	17	bayes	bayes	NOUN
admet-1335	124	18	,	,	PUNCT
admet-1335	124	19	radius	radius	NOUN
admet-1335	124	20	neighbour	neighbour	NOUN
admet-1335	124	21	's	's	PART
admet-1335	124	22	classifier	classifier	NOUN
admet-1335	124	23	,	,	PUNCT
admet-1335	124	24	bagging	bagging	NOUN
admet-1335	124	25	classifier	classifier	NOUN
admet-1335	124	26	,	,	PUNCT
admet-1335	124	27	ada	ada	PROPN
admet-1335	124	28	boost	boost	PROPN
admet-1335	124	29	,	,	PUNCT
admet-1335	124	30	linear	linear	ADJ
admet-1335	124	31	discriminant	discriminant	ADJ
admet-1335	124	32	analysis	analysis	NOUN
admet-1335	124	33	,	,	PUNCT
admet-1335	124	34	quadratic	quadratic	ADJ
admet-1335	124	35	discriminant	discriminant	ADJ
admet-1335	124	36	analysis	analysis	NOUN
admet-1335	124	37	,	,	PUNCT
admet-1335	124	38	extra	extra	ADJ
admet-1335	124	39	tree	tree	NOUN
admet-1335	124	40	classifier	classifier	NOUN
admet-1335	124	41	,	,	PUNCT
admet-1335	124	42	and	and	CCONJ
admet-1335	124	43	lstm	lstm	PROPN
admet-1335	124	44	,	,	PUNCT
admet-1335	124	45	which	which	PRON
admet-1335	124	46	have	have	AUX
admet-1335	124	47	been	be	AUX
admet-1335	124	48	implemented	implement	VERB
admet-1335	124	49	in	in	ADP
admet-1335	124	50	python	python	PROPN
admet-1335	124	51	.	.	PUNCT
admet-1335	125	1	gaussian	gaussian	ADJ
admet-1335	125	2	naive	naive	ADJ
admet-1335	125	3	bayes	bayes	PROPN
admet-1335	125	4	is	be	AUX
admet-1335	125	5	a	a	DET
admet-1335	125	6	statistical	statistical	ADJ
admet-1335	125	7	predictive	predictive	ADJ
admet-1335	125	8	model	model	NOUN
admet-1335	125	9	for	for	ADP
admet-1335	125	10	classification	classification	NOUN
admet-1335	125	11	that	that	PRON
admet-1335	125	12	is	be	AUX
admet-1335	125	13	based	base	VERB
admet-1335	125	14	on	on	ADP
admet-1335	125	15	the	the	DET
admet-1335	125	16	naive	naive	ADJ
admet-1335	125	17	bayes	bayes	NOUN
admet-1335	125	18	algorithm	algorithm	NOUN
admet-1335	125	19	.	.	PUNCT
admet-1335	126	1	for	for	ADP
admet-1335	126	2	our	our	PRON
admet-1335	126	3	dataset	dataset	NOUN
admet-1335	126	4	,	,	PUNCT
admet-1335	126	5	this	this	DET
admet-1335	126	6	algorithm	algorithm	NOUN
admet-1335	126	7	produced	produce	VERB
admet-1335	126	8	an	an	DET
admet-1335	126	9	accuracy	accuracy	NOUN
admet-1335	126	10	of	of	ADP
admet-1335	126	11	64.14	64.14	NUM
admet-1335	126	12	percent	percent	NOUN
admet-1335	126	13	(	(	PUNCT
admet-1335	126	14	table	table	NOUN
admet-1335	126	15	1	1	NUM
admet-1335	126	16	)	)	PUNCT
admet-1335	126	17	.	.	PUNCT
admet-1335	127	1	the	the	DET
admet-1335	127	2	radius	radius	NOUN
admet-1335	127	3	neighbours	neighbours	NOUN
admet-1335	127	4	classifier	classifier	NOUN
admet-1335	127	5	is	be	AUX
admet-1335	127	6	an	an	DET
admet-1335	127	7	extended	extended	ADJ
admet-1335	127	8	version	version	NOUN
admet-1335	127	9	of	of	ADP
admet-1335	127	10	the	the	DET
admet-1335	127	11	knn	knn	PROPN
admet-1335	127	12	algorithm	algorithm	PROPN
admet-1335	127	13	that	that	PRON
admet-1335	127	14	produces	produce	VERB
admet-1335	127	15	results	result	NOUN
admet-1335	127	16	using	use	VERB
admet-1335	127	17	all	all	DET
admet-1335	127	18	instances	instance	NOUN
admet-1335	127	19	within	within	ADP
admet-1335	127	20	a	a	DET
admet-1335	127	21	range	range	NOUN
admet-1335	127	22	of	of	ADP
admet-1335	127	23	a	a	DET
admet-1335	127	24	new	new	ADJ
admet-1335	127	25	instance	instance	NOUN
admet-1335	127	26	rather	rather	ADV
admet-1335	127	27	than	than	ADP
admet-1335	127	28	the	the	DET
admet-1335	127	29	k	k	PROPN
admet-1335	127	30	clusters	cluster	NOUN
admet-1335	127	31	,	,	PUNCT
admet-1335	127	32	which	which	PRON
admet-1335	127	33	would	would	AUX
admet-1335	127	34	be	be	AUX
admet-1335	127	35	beneficial	beneficial	ADJ
admet-1335	127	36	for	for	ADP
admet-1335	127	37	our	our	PRON
admet-1335	127	38	dataset	dataset	NOUN
admet-1335	127	39	,	,	PUNCT
admet-1335	127	40	but	but	CCONJ
admet-1335	127	41	the	the	DET
admet-1335	127	42	model	model	NOUN
admet-1335	127	43	failed	fail	VERB
admet-1335	127	44	to	to	PART
admet-1335	127	45	provide	provide	VERB
admet-1335	127	46	the	the	DET
admet-1335	127	47	expected	expect	VERB
admet-1335	127	48	results	result	NOUN
admet-1335	127	49	,	,	PUNCT
admet-1335	127	50	resulting	result	VERB
admet-1335	127	51	in	in	ADP
admet-1335	127	52	an	an	DET
admet-1335	127	53	accuracy	accuracy	NOUN
admet-1335	127	54	of	of	ADP
admet-1335	127	55	49.2	49.2	NUM
admet-1335	127	56	percent	percent	NOUN
admet-1335	127	57	.	.	PUNCT
admet-1335	128	1	adaboost	adaboost	ADV
admet-1335	128	2	,	,	PUNCT
admet-1335	128	3	also	also	ADV
admet-1335	128	4	known	know	VERB
admet-1335	128	5	as	as	ADP
admet-1335	128	6	adaptive	adaptive	ADJ
admet-1335	128	7	boosting	boosting	NOUN
admet-1335	128	8	,	,	PUNCT
admet-1335	128	9	is	be	AUX
admet-1335	128	10	an	an	DET
admet-1335	128	11	ensemble	ensemble	ADJ
admet-1335	128	12	method	method	NOUN
admet-1335	128	13	.	.	PUNCT
admet-1335	129	1	the	the	DET
admet-1335	129	2	weights	weight	NOUN
admet-1335	129	3	are	be	AUX
admet-1335	129	4	reallocated	reallocate	VERB
admet-1335	129	5	to	to	ADP
admet-1335	129	6	each	each	DET
admet-1335	129	7	instance	instance	NOUN
admet-1335	129	8	,	,	PUNCT
admet-1335	129	9	with	with	ADP
admet-1335	129	10	larger	large	ADJ
admet-1335	129	11	weights	weight	NOUN
admet-1335	129	12	applied	apply	VERB
admet-1335	129	13	to	to	ADP
admet-1335	129	14	inaccurately	inaccurately	ADV
admet-1335	129	15	identified	identify	VERB
admet-1335	129	16	instances	instance	NOUN
admet-1335	129	17	.	.	PUNCT
admet-1335	130	1	boosting	boost	VERB
admet-1335	130	2	is	be	AUX
admet-1335	130	3	used	use	VERB
admet-1335	130	4	in	in	ADP
admet-1335	130	5	supervised	supervised	ADJ
admet-1335	130	6	learning	learn	VERB
admet-1335	130	7	to	to	PART
admet-1335	130	8	minimize	minimize	VERB
admet-1335	130	9	bias	bias	NOUN
admet-1335	130	10	as	as	ADV
admet-1335	130	11	well	well	ADV
admet-1335	130	12	as	as	ADP
admet-1335	130	13	variation	variation	NOUN
admet-1335	130	14	.	.	PUNCT
admet-1335	131	1	the	the	DET
admet-1335	131	2	accuracy	accuracy	NOUN
admet-1335	131	3	of	of	ADP
admet-1335	131	4	this	this	DET
admet-1335	131	5	model	model	NOUN
admet-1335	131	6	was	be	AUX
admet-1335	131	7	76.9	76.9	NUM
admet-1335	131	8	percent	percent	NOUN
admet-1335	131	9	.	.	PUNCT
admet-1335	132	1	linear	linear	ADJ
admet-1335	132	2	and	and	CCONJ
admet-1335	132	3	quadratic	quadratic	ADJ
admet-1335	132	4	discriminant	discriminant	ADJ
admet-1335	132	5	analysis	analysis	NOUN
admet-1335	132	6	resulted	result	VERB
admet-1335	132	7	in	in	ADP
admet-1335	132	8	an	an	DET
admet-1335	132	9	accuracy	accuracy	NOUN
admet-1335	132	10	of	of	ADP
admet-1335	132	11	76.13	76.13	NUM
admet-1335	132	12	and	and	CCONJ
admet-1335	132	13	84.2	84.2	NUM
admet-1335	132	14	percent	percent	NOUN
admet-1335	132	15	.	.	PUNCT
admet-1335	133	1	a	a	DET
admet-1335	133	2	bagging	bagging	NOUN
admet-1335	133	3	classifier	classifier	NOUN
admet-1335	133	4	is	be	AUX
admet-1335	133	5	an	an	DET
admet-1335	133	6	ensemble	ensemble	ADJ
admet-1335	133	7	classifier	classifier	NOUN
admet-1335	133	8	that	that	PRON
admet-1335	133	9	works	work	VERB
admet-1335	133	10	on	on	ADP
admet-1335	133	11	random	random	ADJ
admet-1335	133	12	samples	sample	NOUN
admet-1335	133	13	of	of	ADP
admet-1335	133	14	the	the	DET
admet-1335	133	15	data	datum	NOUN
admet-1335	133	16	and	and	CCONJ
admet-1335	133	17	then	then	ADV
admet-1335	133	18	combines	combine	VERB
admet-1335	133	19	various	various	ADJ
admet-1335	133	20	instances	instance	NOUN
admet-1335	133	21	to	to	PART
admet-1335	133	22	obtain	obtain	VERB
admet-1335	133	23	the	the	DET
admet-1335	133	24	final	final	ADJ
admet-1335	133	25	output	output	NOUN
admet-1335	133	26	.	.	PUNCT
admet-1335	134	1	this	this	DET
admet-1335	134	2	method	method	NOUN
admet-1335	134	3	resulted	result	VERB
admet-1335	134	4	in	in	ADP
admet-1335	134	5	an	an	DET
admet-1335	134	6	accuracy	accuracy	NOUN
admet-1335	134	7	of	of	ADP
admet-1335	134	8	85.8	85.8	NUM
admet-1335	134	9	percent	percent	NOUN
admet-1335	134	10	.	.	PUNCT
admet-1335	135	1	extra	extra	ADJ
admet-1335	135	2	tree	tree	NOUN
admet-1335	135	3	classifier	classifier	NOUN
admet-1335	135	4	,	,	PUNCT
admet-1335	135	5	an	an	DET
admet-1335	135	6	extended	extended	ADJ
admet-1335	135	7	version	version	NOUN
admet-1335	135	8	of	of	ADP
admet-1335	135	9	the	the	DET
admet-1335	135	10	random	random	ADJ
admet-1335	135	11	forest	forest	NOUN
admet-1335	135	12	algorithm	algorithm	NOUN
admet-1335	135	13	,	,	PUNCT
admet-1335	135	14	resulted	result	VERB
admet-1335	135	15	in	in	ADP
admet-1335	135	16	an	an	DET
admet-1335	135	17	accuracy	accuracy	NOUN
admet-1335	135	18	of	of	ADP
admet-1335	135	19	90	90	NUM
admet-1335	135	20	percent	percent	NOUN
admet-1335	135	21	.	.	PUNCT
admet-1335	136	1	lstm	lstm	PROPN
admet-1335	136	2	model	model	PROPN
admet-1335	136	3	resulted	result	VERB
admet-1335	136	4	in	in	ADP
admet-1335	136	5	an	an	DET
admet-1335	136	6	accuracy	accuracy	NOUN
admet-1335	136	7	of	of	ADP
admet-1335	136	8	91.5	91.5	NUM
admet-1335	136	9	percent	percent	NOUN
admet-1335	136	10	.	.	PUNCT
admet-1335	137	1	table	table	NOUN
admet-1335	137	2	1	1	NUM
admet-1335	137	3	.	.	PUNCT
admet-1335	138	1	analysis	analysis	NOUN
admet-1335	138	2	of	of	ADP
admet-1335	138	3	the	the	DET
admet-1335	138	4	effectiveness	effectiveness	NOUN
admet-1335	138	5	of	of	ADP
admet-1335	138	6	different	different	ADJ
admet-1335	138	7	classifiers	classifier	NOUN
admet-1335	138	8	method	method	VERB
admet-1335	138	9	accuracy	accuracy	NOUN
admet-1335	138	10	precision	precision	NOUN
admet-1335	138	11	recall	recall	VERB
admet-1335	138	12	f1	f1	NOUN
admet-1335	138	13	-	-	PUNCT
admet-1335	138	14	score	score	NOUN
admet-1335	138	15	gaussian	gaussian	NOUN
admet-1335	138	16	naive	naive	ADJ
admet-1335	138	17	bayes	bayes	NOUN
admet-1335	138	18	64.14	64.14	NUM
admet-1335	138	19	0.74	0.74	NUM
admet-1335	138	20	0.46	0.46	NUM
admet-1335	138	21	0.56	0.56	NUM
admet-1335	138	22	radius	radius	NOUN
admet-1335	138	23	neighbours	neighbour	NOUN
admet-1335	138	24	classifier	classifier	NOUN
admet-1335	138	25	49.2	49.2	NUM
admet-1335	138	26	0.49	0.49	NUM
admet-1335	138	27	1.00	1.00	NUM
admet-1335	138	28	0.66	0.66	NUM
admet-1335	138	29	ada	ada	PROPN
admet-1335	138	30	boost	boost	VERB
admet-1335	138	31	76.9	76.9	NUM
admet-1335	138	32	0.79	0.79	NUM
admet-1335	138	33	0.75	0.75	NUM
admet-1335	138	34	0.77	0.77	NUM
admet-1335	138	35	linear	linear	ADJ
admet-1335	138	36	discriminant	discriminant	ADJ
admet-1335	138	37	analysis	analysis	NOUN
admet-1335	138	38	76.13	76.13	NUM
admet-1335	138	39	0.80	0.80	NUM
admet-1335	138	40	0.71	0.71	NUM
admet-1335	138	41	0.75	0.75	NUM
admet-1335	138	42	quadratic	quadratic	ADJ
admet-1335	138	43	discriminant	discriminant	NOUN
admet-1335	138	44	analysis	analysis	NOUN
admet-1335	138	45	84.2	84.2	NUM
admet-1335	138	46	0.93	0.93	NUM
admet-1335	138	47	0.74	0.74	NUM
admet-1335	138	48	0.83	0.83	NUM
admet-1335	138	49	bagging	bagging	NOUN
admet-1335	138	50	classifier	classifier	NOUN
admet-1335	138	51	85.8	85.8	NUM
admet-1335	138	52	0.89	0.89	NUM
admet-1335	138	53	0.86	0.86	NUM
admet-1335	138	54	0.88	0.88	NUM
admet-1335	138	55	extra	extra	ADJ
admet-1335	138	56	tree	tree	NOUN
admet-1335	138	57	classifier	classifier	NOUN
admet-1335	138	58	90	90	NUM
admet-1335	138	59	0.95	0.95	NUM
admet-1335	138	60	0.85	0.85	NUM
admet-1335	138	61	0.90	0.90	NUM
admet-1335	138	62	lstm	lstm	NOUN
admet-1335	138	63	(	(	PUNCT
admet-1335	138	64	long	long	ADJ
admet-1335	138	65	short	short	ADJ
admet-1335	138	66	-	-	PUNCT
admet-1335	138	67	term	term	NOUN
admet-1335	138	68	memory	memory	NOUN
admet-1335	138	69	)	)	PUNCT
admet-1335	138	70	91.5	91.5	NUM
admet-1335	138	71	0.91	0.91	NUM
admet-1335	138	72	0.91	0.91	NUM
admet-1335	138	73	0.91	0.91	NUM
admet-1335	138	74	table	table	NOUN
admet-1335	138	75	1	1	NUM
admet-1335	138	76	represents	represent	VERB
admet-1335	138	77	the	the	DET
admet-1335	138	78	results	result	NOUN
admet-1335	138	79	of	of	ADP
admet-1335	138	80	performance	performance	NOUN
admet-1335	138	81	evaluation	evaluation	NOUN
admet-1335	138	82	metrics	metric	NOUN
admet-1335	138	83	and	and	CCONJ
admet-1335	138	84	accuracy	accuracy	NOUN
admet-1335	138	85	of	of	ADP
admet-1335	138	86	all	all	DET
admet-1335	138	87	the	the	DET
admet-1335	138	88	algorithms	algorithm	NOUN
admet-1335	138	89	implemented	implement	VERB
admet-1335	138	90	.	.	PUNCT
admet-1335	139	1	it	it	PRON
admet-1335	139	2	is	be	AUX
admet-1335	139	3	evident	evident	ADJ
admet-1335	139	4	that	that	SCONJ
admet-1335	139	5	the	the	DET
admet-1335	139	6	lstm	lstm	NOUN
admet-1335	139	7	approach	approach	NOUN
admet-1335	139	8	is	be	AUX
admet-1335	139	9	superior	superior	ADJ
admet-1335	139	10	and	and	CCONJ
admet-1335	139	11	has	have	VERB
admet-1335	139	12	consistent	consistent	ADJ
admet-1335	139	13	performance	performance	NOUN
admet-1335	139	14	across	across	ADP
admet-1335	139	15	all	all	DET
admet-1335	139	16	measures	measure	NOUN
admet-1335	139	17	.	.	PUNCT
admet-1335	140	1	so	so	ADV
admet-1335	140	2	,	,	PUNCT
admet-1335	140	3	lstm	lstm	NOUN
admet-1335	140	4	has	have	AUX
admet-1335	140	5	been	be	AUX
admet-1335	140	6	considered	consider	VERB
admet-1335	140	7	for	for	ADP
admet-1335	140	8	protein	protein	NOUN
admet-1335	140	9	allergen	allergen	NOUN
admet-1335	140	10	prediction	prediction	NOUN
admet-1335	140	11	.	.	PUNCT
admet-1335	141	1	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	141	2	pallavi	pallavi	NOUN
admet-1335	141	3	and	and	CCONJ
admet-1335	141	4	rakshitha	rakshitha	PROPN
admet-1335	141	5	admet	admet	PROPN
admet-1335	141	6	&	&	CCONJ
admet-1335	141	7	dmpk	dmpk	PROPN
admet-1335	141	8	10(3	10(3	NUM
admet-1335	141	9	)	)	PUNCT
admet-1335	141	10	(	(	PUNCT
admet-1335	141	11	2022	2022	NUM
admet-1335	141	12	)	)	PUNCT
admet-1335	141	13	231	231	NUM
admet-1335	141	14	-	-	SYM
admet-1335	141	15	240	240	NUM
admet-1335	141	16	236	236	NUM
admet-1335	141	17	table	table	NOUN
admet-1335	141	18	2	2	NUM
admet-1335	141	19	.	.	PUNCT
admet-1335	141	20	analysis	analysis	NOUN
admet-1335	141	21	of	of	ADP
admet-1335	141	22	the	the	DET
admet-1335	141	23	classification	classification	NOUN
admet-1335	141	24	results	result	NOUN
admet-1335	141	25	of	of	ADP
admet-1335	141	26	different	different	ADJ
admet-1335	141	27	classifiers	classifier	NOUN
admet-1335	141	28	based	base	VERB
admet-1335	141	29	on	on	ADP
admet-1335	141	30	training	training	NOUN
admet-1335	141	31	and	and	CCONJ
admet-1335	141	32	testing	testing	NOUN
admet-1335	141	33	data	datum	NOUN
admet-1335	141	34	.	.	PUNCT
admet-1335	142	1	method	method	NOUN
admet-1335	142	2	training	training	NOUN
admet-1335	142	3	data	datum	NOUN
admet-1335	142	4	testing	testing	NOUN
admet-1335	142	5	data	datum	NOUN
admet-1335	142	6	gaussian	gaussian	VERB
admet-1335	142	7	naive	naive	ADJ
admet-1335	142	8	bayes	bayes	NOUN
admet-1335	142	9	63.8	63.8	NUM
admet-1335	142	10	59.7	59.7	NUM
admet-1335	142	11	radius	radius	NOUN
admet-1335	142	12	neighbours	neighbour	NOUN
admet-1335	142	13	classifier	classifier	NOUN
admet-1335	142	14	50.5	50.5	NUM
admet-1335	142	15	47.6	47.6	NUM
admet-1335	142	16	ada	ada	PROPN
admet-1335	142	17	boost	boost	VERB
admet-1335	142	18	84.6	84.6	NUM
admet-1335	142	19	78.1	78.1	NUM
admet-1335	142	20	linear	linear	ADJ
admet-1335	142	21	discriminant	discriminant	NOUN
admet-1335	142	22	analysis	analysis	NOUN
admet-1335	142	23	78.6	78.6	NUM
admet-1335	142	24	74.9	74.9	NUM
admet-1335	142	25	quadratic	quadratic	ADJ
admet-1335	142	26	discriminant	discriminant	NOUN
admet-1335	142	27	analysis	analysis	NOUN
admet-1335	142	28	88.7	88.7	NUM
admet-1335	142	29	81.6	81.6	NUM
admet-1335	142	30	bagging	bagging	NOUN
admet-1335	142	31	classifier	classifier	NOUN
admet-1335	142	32	88.4	88.4	NUM
admet-1335	142	33	86.3	86.3	NUM
admet-1335	142	34	extra	extra	ADJ
admet-1335	142	35	tree	tree	NOUN
admet-1335	142	36	classifier	classifier	NOUN
admet-1335	142	37	93.4	93.4	NUM
admet-1335	142	38	89.8	89.8	NUM
admet-1335	142	39	lstm	lstm	NOUN
admet-1335	142	40	(	(	PUNCT
admet-1335	142	41	long	long	ADJ
admet-1335	142	42	short	short	ADJ
admet-1335	142	43	-	-	PUNCT
admet-1335	142	44	term	term	NOUN
admet-1335	142	45	memory	memory	NOUN
admet-1335	142	46	)	)	PUNCT
admet-1335	142	47	94.1	94.1	NUM
admet-1335	142	48	91.5	91.5	NUM
admet-1335	142	49	table	table	NOUN
admet-1335	142	50	2	2	NUM
admet-1335	142	51	represents	represent	VERB
admet-1335	142	52	the	the	DET
admet-1335	142	53	accuracy	accuracy	NOUN
admet-1335	142	54	of	of	ADP
admet-1335	142	55	the	the	DET
admet-1335	142	56	algorithms	algorithm	NOUN
admet-1335	142	57	for	for	ADP
admet-1335	142	58	training	training	NOUN
admet-1335	142	59	and	and	CCONJ
admet-1335	142	60	testing	testing	NOUN
admet-1335	142	61	dataset	dataset	NOUN
admet-1335	142	62	.	.	PUNCT
admet-1335	143	1	the	the	DET
admet-1335	143	2	lstm	lstm	PROPN
admet-1335	143	3	method	method	NOUN
admet-1335	143	4	was	be	AUX
admet-1335	143	5	implemented	implement	VERB
admet-1335	143	6	to	to	ADP
admet-1335	143	7	a	a	DET
admet-1335	143	8	well	well	ADV
admet-1335	143	9	-	-	PUNCT
admet-1335	143	10	known	know	VERB
admet-1335	143	11	benchmark	benchmark	NOUN
admet-1335	143	12	data	datum	NOUN
admet-1335	143	13	set	set	VERB
admet-1335	143	14	for	for	ADP
admet-1335	143	15	protein	protein	NOUN
admet-1335	143	16	allergen	allergen	NOUN
admet-1335	143	17	identification	identification	NOUN
admet-1335	143	18	,	,	PUNCT
admet-1335	143	19	in	in	ADP
admet-1335	143	20	which	which	PRON
admet-1335	143	21	a	a	DET
admet-1335	143	22	protein	protein	NOUN
admet-1335	143	23	has	have	VERB
admet-1335	143	24	to	to	PART
admet-1335	143	25	be	be	AUX
admet-1335	143	26	classified	classify	VERB
admet-1335	143	27	as	as	ADP
admet-1335	143	28	allergen	allergen	NOUN
admet-1335	143	29	or	or	CCONJ
admet-1335	143	30	non	non	ADJ
admet-1335	143	31	-	-	NOUN
admet-1335	143	32	allergen	allergen	NOUN
admet-1335	143	33	.	.	PUNCT
admet-1335	144	1	lstm	lstm	NOUN
admet-1335	144	2	delivers	deliver	VERB
admet-1335	144	3	highly	highly	ADV
admet-1335	144	4	defined	define	VERB
admet-1335	144	5	classification	classification	NOUN
admet-1335	144	6	performance	performance	NOUN
admet-1335	144	7	that	that	PRON
admet-1335	144	8	is	be	AUX
admet-1335	144	9	substantially	substantially	ADV
admet-1335	144	10	quicker	quick	ADJ
admet-1335	144	11	than	than	ADP
admet-1335	144	12	other	other	ADJ
admet-1335	144	13	algorithms	algorithm	NOUN
admet-1335	144	14	with	with	ADP
admet-1335	144	15	comparable	comparable	ADJ
admet-1335	144	16	classification	classification	NOUN
admet-1335	144	17	performance	performance	NOUN
admet-1335	144	18	.	.	PUNCT
admet-1335	145	1	lstm	lstm	NOUN
admet-1335	145	2	is	be	AUX
admet-1335	145	3	five	five	NUM
admet-1335	145	4	times	time	NOUN
admet-1335	145	5	faster	fast	ADJ
admet-1335	145	6	than	than	ADP
admet-1335	145	7	marginal	marginal	ADJ
admet-1335	145	8	classification	classification	NOUN
admet-1335	145	9	algorithms	algorithm	NOUN
admet-1335	145	10	(	(	PUNCT
admet-1335	145	11	methods	method	NOUN
admet-1335	145	12	based	base	VERB
admet-1335	145	13	on	on	ADP
admet-1335	145	14	distance	distance	NOUN
admet-1335	145	15	)	)	PUNCT
admet-1335	145	16	and	and	CCONJ
admet-1335	145	17	two	two	NUM
admet-1335	145	18	times	time	NOUN
admet-1335	145	19	faster	fast	ADJ
admet-1335	145	20	than	than	ADP
admet-1335	145	21	the	the	DET
admet-1335	145	22	quickest	quick	ADJ
admet-1335	145	23	svm	svm	ADJ
admet-1335	145	24	-	-	PUNCT
admet-1335	145	25	based	base	VERB
admet-1335	145	26	methods	method	NOUN
admet-1335	145	27	(	(	PUNCT
admet-1335	145	28	which	which	PRON
admet-1335	145	29	have	have	VERB
admet-1335	145	30	lower	low	ADJ
admet-1335	145	31	classification	classification	NOUN
admet-1335	145	32	performance	performance	NOUN
admet-1335	145	33	than	than	ADP
admet-1335	145	34	lstm	lstm	ADJ
admet-1335	145	35	)	)	PUNCT
admet-1335	145	36	.	.	PUNCT
admet-1335	146	1	all	all	DET
admet-1335	146	2	the	the	DET
admet-1335	146	3	implemented	implement	VERB
admet-1335	146	4	methods	method	NOUN
admet-1335	146	5	were	be	AUX
admet-1335	146	6	tested	test	VERB
admet-1335	146	7	and	and	CCONJ
admet-1335	146	8	compared	compare	VERB
admet-1335	146	9	using	use	VERB
admet-1335	146	10	performance	performance	NOUN
admet-1335	146	11	evaluation	evaluation	NOUN
admet-1335	146	12	measures	measure	NOUN
admet-1335	146	13	.	.	PUNCT
admet-1335	147	1	the	the	DET
admet-1335	147	2	top	top	ADV
admet-1335	147	3	-	-	PUNCT
admet-1335	147	4	performing	perform	VERB
admet-1335	147	5	model	model	NOUN
admet-1335	147	6	was	be	AUX
admet-1335	147	7	lstm	lstm	ADJ
admet-1335	147	8	,	,	PUNCT
admet-1335	147	9	which	which	PRON
admet-1335	147	10	had	have	VERB
admet-1335	147	11	an	an	DET
admet-1335	147	12	accuracy	accuracy	NOUN
admet-1335	147	13	of	of	ADP
admet-1335	147	14	91.51	91.51	NUM
admet-1335	147	15	percent	percent	NOUN
admet-1335	147	16	.	.	PUNCT
admet-1335	148	1	lstm	lstm	NOUN
admet-1335	148	2	is	be	AUX
admet-1335	148	3	a	a	DET
admet-1335	148	4	more	more	ADV
admet-1335	148	5	sophisticated	sophisticated	ADJ
admet-1335	148	6	version	version	NOUN
admet-1335	148	7	of	of	ADP
admet-1335	148	8	the	the	DET
admet-1335	148	9	rnn	rnn	NOUN
admet-1335	148	10	(	(	PUNCT
admet-1335	148	11	recurrent	recurrent	ADJ
admet-1335	148	12	neural	neural	ADJ
admet-1335	148	13	network	network	NOUN
admet-1335	148	14	)	)	PUNCT
admet-1335	148	15	.	.	PUNCT
admet-1335	149	1	the	the	DET
admet-1335	149	2	lstm	lstm	NOUN
admet-1335	149	3	has	have	AUX
admet-1335	149	4	been	be	AUX
admet-1335	149	5	considered	consider	VERB
admet-1335	149	6	for	for	ADP
admet-1335	149	7	our	our	PRON
admet-1335	149	8	problem	problem	NOUN
admet-1335	149	9	because	because	SCONJ
admet-1335	149	10	of	of	ADP
admet-1335	149	11	its	its	PRON
admet-1335	149	12	robustness	robustness	NOUN
admet-1335	149	13	against	against	ADP
admet-1335	149	14	long	long	ADJ
admet-1335	149	15	-	-	PUNCT
admet-1335	149	16	term	term	NOUN
admet-1335	149	17	dependency	dependency	NOUN
admet-1335	149	18	problems	problem	NOUN
admet-1335	149	19	.	.	PUNCT
admet-1335	150	1	since	since	SCONJ
admet-1335	150	2	the	the	DET
admet-1335	150	3	protein	protein	NOUN
admet-1335	150	4	sequences	sequence	NOUN
admet-1335	150	5	are	be	AUX
admet-1335	150	6	also	also	ADV
admet-1335	150	7	correlated	correlate	VERB
admet-1335	150	8	with	with	ADP
admet-1335	150	9	each	each	DET
admet-1335	150	10	other	other	ADJ
admet-1335	150	11	,	,	PUNCT
admet-1335	150	12	lstm	lstm	PROPN
admet-1335	150	13	would	would	AUX
admet-1335	150	14	be	be	AUX
admet-1335	150	15	a	a	DET
admet-1335	150	16	likely	likely	ADJ
admet-1335	150	17	method	method	NOUN
admet-1335	150	18	for	for	ADP
admet-1335	150	19	solving	solve	VERB
admet-1335	150	20	long	long	ADJ
admet-1335	150	21	-	-	PUNCT
admet-1335	150	22	term	term	NOUN
admet-1335	150	23	dependencies	dependency	NOUN
admet-1335	150	24	and	and	CCONJ
admet-1335	150	25	would	would	AUX
admet-1335	150	26	overcome	overcome	VERB
admet-1335	150	27	the	the	DET
admet-1335	150	28	drawbacks	drawback	NOUN
admet-1335	150	29	of	of	ADP
admet-1335	150	30	the	the	DET
admet-1335	150	31	alignment	alignment	NOUN
admet-1335	150	32	method	method	NOUN
admet-1335	150	33	.	.	PUNCT
admet-1335	151	1	table	table	NOUN
admet-1335	151	2	3	3	NUM
admet-1335	151	3	.	.	NOUN
admet-1335	151	4	assessment	assessment	NOUN
admet-1335	151	5	of	of	ADP
admet-1335	151	6	web	web	NOUN
admet-1335	151	7	servers	server	NOUN
admet-1335	151	8	for	for	ADP
admet-1335	151	9	allergenicity	allergenicity	NOUN
admet-1335	151	10	prediction	prediction	NOUN
admet-1335	151	11	in	in	ADP
admet-1335	151	12	table	table	NOUN
admet-1335	151	13	3	3	NUM
admet-1335	151	14	the	the	DET
admet-1335	151	15	performance	performance	NOUN
admet-1335	151	16	of	of	ADP
admet-1335	151	17	the	the	DET
admet-1335	151	18	lstm	lstm	PROPN
admet-1335	151	19	model	model	NOUN
admet-1335	151	20	was	be	AUX
admet-1335	151	21	compared	compare	VERB
admet-1335	151	22	to	to	ADP
admet-1335	151	23	nine	nine	NUM
admet-1335	151	24	freely	freely	ADV
admet-1335	151	25	available	available	ADJ
admet-1335	151	26	servers	server	NOUN
admet-1335	151	27	.	.	PUNCT
admet-1335	152	1	the	the	DET
admet-1335	152	2	lstm	lstm	NOUN
admet-1335	152	3	resulted	result	VERB
admet-1335	152	4	in	in	ADP
admet-1335	152	5	an	an	DET
admet-1335	152	6	accuracy	accuracy	NOUN
admet-1335	152	7	of	of	ADP
admet-1335	152	8	91.5	91.5	NUM
admet-1335	152	9	percent	percent	NOUN
admet-1335	152	10	.	.	PUNCT
admet-1335	153	1	a	a	DET
admet-1335	153	2	roc	roc	PROPN
admet-1335	153	3	curve	curve	NOUN
admet-1335	153	4	(	(	PUNCT
admet-1335	153	5	short	short	ADJ
admet-1335	153	6	for	for	ADP
admet-1335	153	7	receiver	receiver	NOUN
admet-1335	153	8	operating	operate	VERB
admet-1335	153	9	characteristic	characteristic	NOUN
admet-1335	153	10	)	)	PUNCT
admet-1335	153	11	plots	plot	VERB
admet-1335	153	12	the	the	DET
admet-1335	153	13	rate	rate	NOUN
admet-1335	153	14	of	of	ADP
admet-1335	153	15	true	true	ADJ
admet-1335	153	16	positives	positive	NOUN
admet-1335	153	17	vs.	vs.	ADP
admet-1335	153	18	false	false	ADJ
admet-1335	153	19	positives	positive	NOUN
admet-1335	153	20	to	to	PART
admet-1335	153	21	assess	assess	VERB
admet-1335	153	22	the	the	DET
admet-1335	153	23	effectiveness	effectiveness	NOUN
admet-1335	153	24	of	of	ADP
admet-1335	153	25	a	a	DET
admet-1335	153	26	classification	classification	NOUN
admet-1335	153	27	model	model	NOUN
admet-1335	153	28	.	.	PUNCT
admet-1335	154	1	auc	auc	NOUN
admet-1335	154	2	measures	measure	NOUN
admet-1335	154	3	how	how	SCONJ
admet-1335	154	4	well	well	ADV
admet-1335	154	5	a	a	DET
admet-1335	154	6	model	model	NOUN
admet-1335	154	7	distinguishes	distinguish	VERB
admet-1335	154	8	between	between	ADP
admet-1335	154	9	positive	positive	ADJ
admet-1335	154	10	and	and	CCONJ
admet-1335	154	11	negative	negative	ADJ
admet-1335	154	12	classes	class	NOUN
admet-1335	154	13	.	.	PUNCT
admet-1335	155	1	auc	auc	NOUN
admet-1335	155	2	is	be	AUX
admet-1335	155	3	not	not	PART
admet-1335	155	4	affected	affect	VERB
admet-1335	155	5	by	by	ADP
admet-1335	155	6	the	the	DET
admet-1335	155	7	classification	classification	NOUN
admet-1335	155	8	threshold	threshold	NOUN
admet-1335	155	9	value	value	NOUN
admet-1335	155	10	.	.	PUNCT
admet-1335	156	1	modifying	modify	VERB
admet-1335	156	2	the	the	DET
admet-1335	156	3	threshold	threshold	NOUN
admet-1335	156	4	value	value	NOUN
admet-1335	156	5	does	do	AUX
admet-1335	156	6	not	not	PART
admet-1335	156	7	affect	affect	VERB
admet-1335	156	8	auc	auc	NOUN
admet-1335	156	9	because	because	SCONJ
admet-1335	156	10	it	it	PRON
admet-1335	156	11	is	be	AUX
admet-1335	156	12	an	an	DET
admet-1335	156	13	aggregate	aggregate	ADJ
admet-1335	156	14	measure	measure	NOUN
admet-1335	156	15	of	of	ADP
admet-1335	156	16	roc	roc	PROPN
admet-1335	156	17	.	.	PROPN
admet-1335	156	18	figure	figure	NOUN
admet-1335	156	19	3	3	NUM
admet-1335	156	20	indicates	indicate	VERB
admet-1335	156	21	that	that	SCONJ
admet-1335	156	22	when	when	SCONJ
admet-1335	156	23	the	the	DET
admet-1335	156	24	true	true	ADJ
admet-1335	156	25	positive	positive	ADJ
admet-1335	156	26	rate	rate	NOUN
admet-1335	156	27	increases	increase	NOUN
admet-1335	156	28	,	,	PUNCT
admet-1335	156	29	so	so	ADV
admet-1335	156	30	does	do	VERB
admet-1335	156	31	the	the	DET
admet-1335	156	32	false	false	ADJ
admet-1335	156	33	positive	positive	ADJ
admet-1335	156	34	rate	rate	NOUN
admet-1335	156	35	and	and	CCONJ
admet-1335	156	36	after	after	ADP
admet-1335	156	37	a	a	DET
admet-1335	156	38	certain	certain	ADJ
admet-1335	156	39	point	point	NOUN
admet-1335	156	40	that	that	PRON
admet-1335	156	41	is	be	AUX
admet-1335	156	42	near	near	ADP
admet-1335	156	43	0.91	0.91	NUM
admet-1335	156	44	the	the	DET
admet-1335	156	45	graph	graph	NOUN
admet-1335	156	46	is	be	AUX
admet-1335	156	47	constant	constant	ADJ
admet-1335	156	48	.	.	PUNCT
admet-1335	157	1	the	the	DET
admet-1335	157	2	area	area	NOUN
admet-1335	157	3	under	under	ADP
admet-1335	157	4	the	the	DET
admet-1335	157	5	roc	roc	PROPN
admet-1335	157	6	curve	curve	NOUN
admet-1335	157	7	between	between	ADP
admet-1335	157	8	(	(	PUNCT
admet-1335	157	9	0,0	0,0	NOUN
admet-1335	157	10	)	)	PUNCT
admet-1335	157	11	and	and	CCONJ
admet-1335	157	12	(	(	PUNCT
admet-1335	157	13	1,1	1,1	NUM
admet-1335	157	14	)	)	PUNCT
admet-1335	157	15	is	be	AUX
admet-1335	157	16	defined	define	VERB
admet-1335	157	17	as	as	ADP
admet-1335	157	18	the	the	DET
admet-1335	157	19	area	area	NOUN
admet-1335	157	20	under	under	ADP
admet-1335	157	21	the	the	DET
admet-1335	157	22	curve	curve	NOUN
admet-1335	157	23	(	(	PUNCT
admet-1335	157	24	auc	auc	NOUN
admet-1335	157	25	)	)	PUNCT
admet-1335	157	26	.	.	PUNCT
admet-1335	158	1	auc	auc	NOUN
admet-1335	158	2	essentially	essentially	ADV
admet-1335	158	3	aggregates	aggregate	VERB
admet-1335	158	4	the	the	DET
admet-1335	158	5	model	model	NOUN
admet-1335	158	6	's	's	PART
admet-1335	158	7	performance	performance	NOUN
admet-1335	158	8	overall	overall	ADJ
admet-1335	158	9	threshold	threshold	NOUN
admet-1335	158	10	values	value	NOUN
admet-1335	158	11	.	.	PUNCT
admet-1335	159	1	the	the	DET
admet-1335	159	2	lstm	lstm	PROPN
admet-1335	159	3	model	model	NOUN
admet-1335	159	4	has	have	VERB
admet-1335	159	5	the	the	DET
admet-1335	159	6	highest	high	ADJ
admet-1335	159	7	auc	auc	NOUN
admet-1335	159	8	,	,	PUNCT
admet-1335	159	9	indicating	indicate	VERB
admet-1335	159	10	that	that	SCONJ
admet-1335	159	11	it	it	PRON
admet-1335	159	12	has	have	VERB
admet-1335	159	13	the	the	DET
admet-1335	159	14	largest	large	ADJ
admet-1335	159	15	area	area	NOUN
admet-1335	159	16	under	under	ADP
admet-1335	159	17	the	the	DET
admet-1335	159	18	curve	curve	NOUN
admet-1335	159	19	and	and	CCONJ
admet-1335	159	20	is	be	AUX
admet-1335	159	21	the	the	DET
admet-1335	159	22	best	good	ADJ
admet-1335	159	23	model	model	NOUN
admet-1335	159	24	for	for	ADP
admet-1335	159	25	correctly	correctly	ADV
admet-1335	159	26	classifying	classify	VERB
admet-1335	159	27	observations	observation	NOUN
admet-1335	159	28	.	.	PUNCT
admet-1335	160	1	the	the	DET
admet-1335	160	2	software	software	NOUN
admet-1335	160	3	for	for	ADP
admet-1335	160	4	the	the	DET
admet-1335	160	5	server	server	NOUN
admet-1335	160	6	proall	proall	NOUN
admet-1335	160	7	-	-	PUNCT
admet-1335	160	8	d	d	PROPN
admet-1335	160	9	has	have	AUX
admet-1335	160	10	been	be	AUX
admet-1335	160	11	developed	develop	VERB
admet-1335	160	12	to	to	PART
admet-1335	160	13	predict	predict	VERB
admet-1335	160	14	potential	potential	ADJ
admet-1335	160	15	allergens	allergen	NOUN
admet-1335	160	16	using	use	VERB
admet-1335	160	17	the	the	DET
admet-1335	160	18	lstm	lstm	ADJ
admet-1335	160	19	algorithm	algorithm	NOUN
admet-1335	160	20	.	.	PUNCT
admet-1335	161	1	it	it	PRON
admet-1335	161	2	is	be	AUX
admet-1335	161	3	developed	develop	VERB
admet-1335	161	4	using	use	VERB
admet-1335	161	5	the	the	DET
admet-1335	161	6	python	python	NOUN
admet-1335	161	7	django	django	NOUN
admet-1335	161	8	framework	framework	NOUN
admet-1335	161	9	,	,	PUNCT
admet-1335	161	10	which	which	PRON
admet-1335	161	11	is	be	AUX
admet-1335	161	12	fast	fast	ADJ
admet-1335	161	13	and	and	CCONJ
admet-1335	161	14	user	user	NOUN
admet-1335	161	15	-	-	PUNCT
admet-1335	161	16	friendly	friendly	ADJ
admet-1335	161	17	.	.	PUNCT
admet-1335	162	1	server	server	NOUN
admet-1335	162	2	accuracy	accuracy	NOUN
admet-1335	162	3	allerhunter	allerhunter	NOUN
admet-1335	162	4	0.871	0.871	NUM
admet-1335	162	5	algpred	algpre	VERB
admet-1335	162	6	(	(	PUNCT
admet-1335	162	7	svm_single_aa	svm_single_aa	PROPN
admet-1335	162	8	)	)	PUNCT
admet-1335	162	9	0.775	0.775	NUM
admet-1335	162	10	algpred	algpre	VERB
admet-1335	162	11	(	(	PUNCT
admet-1335	162	12	svm_dipeptide	svm_dipeptide	NOUN
admet-1335	162	13	)	)	PUNCT
admet-1335	162	14	0.796	0.796	NUM
admet-1335	162	15	algpred(arp	algpred(arp	NOUN
admet-1335	162	16	)	)	PUNCT
admet-1335	162	17	0.842	0.842	NUM
admet-1335	162	18	appel	appel	X
admet-1335	162	19	0.783	0.783	NUM
admet-1335	162	20	proap(motif	proap(motif	PROPN
admet-1335	162	21	)	)	PUNCT
admet-1335	162	22	0.505	0.505	NUM
admet-1335	162	23	proap(svm	proap(svm	NOUN
admet-1335	162	24	)	)	PUNCT
admet-1335	162	25	0.843	0.843	NUM
admet-1335	162	26	allertop	allertop	NOUN
admet-1335	162	27	v.1	v.1	ADP
admet-1335	162	28	0.828	0.828	NUM
admet-1335	162	29	allergenfp	allergenfp	NOUN
admet-1335	162	30	0.879	0.879	NUM
admet-1335	162	31	allertop	allertop	NOUN
admet-1335	162	32	v.2	v.2	NOUN
admet-1335	162	33	0.887	0.887	NUM
admet-1335	162	34	lstm	lstm	NOUN
admet-1335	162	35	model	model	NOUN
admet-1335	162	36	0.915	0.915	NUM
admet-1335	162	37	admet	admet	PROPN
admet-1335	162	38	&	&	CCONJ
admet-1335	162	39	dmpk	dmpk	PROPN
admet-1335	162	40	10(3	10(3	NUM
admet-1335	162	41	)	)	PUNCT
admet-1335	162	42	(	(	PUNCT
admet-1335	162	43	2022	2022	NUM
admet-1335	162	44	)	)	PUNCT
admet-1335	162	45	231	231	NUM
admet-1335	162	46	-	-	SYM
admet-1335	162	47	240	240	NUM
admet-1335	162	48	proall	proall	NOUN
admet-1335	162	49	-	-	PUNCT
admet-1335	162	50	d	d	NOUN
admet-1335	162	51	:	:	PUNCT
admet-1335	162	52	protein	protein	NOUN
admet-1335	162	53	allergen	allergen	NOUN
admet-1335	162	54	detection	detection	NOUN
admet-1335	162	55	doi	doi	NOUN
admet-1335	162	56	:	:	PUNCT
admet-1335	162	57	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	162	58	237	237	NUM
admet-1335	162	59	figure	figure	NOUN
admet-1335	162	60	3	3	NUM
admet-1335	162	61	.	.	PUNCT
admet-1335	163	1	the	the	DET
admet-1335	163	2	lstm	lstm	PROPN
admet-1335	163	3	model	model	PROPN
admet-1335	163	4	’s	’s	PART
admet-1335	163	5	roc	roc	PROPN
admet-1335	163	6	curve	curve	NOUN
admet-1335	163	7	there	there	PRON
admet-1335	163	8	are	be	VERB
admet-1335	163	9	three	three	NUM
admet-1335	163	10	different	different	ADJ
admet-1335	163	11	sections	section	NOUN
admet-1335	163	12	,	,	PUNCT
admet-1335	163	13	namely	namely	ADV
admet-1335	163	14	home	home	NOUN
admet-1335	163	15	,	,	PUNCT
admet-1335	163	16	datasets	dataset	NOUN
admet-1335	163	17	,	,	PUNCT
admet-1335	163	18	and	and	CCONJ
admet-1335	163	19	method	method	ADJ
admet-1335	163	20	description	description	NOUN
admet-1335	163	21	as	as	SCONJ
admet-1335	163	22	shown	show	VERB
admet-1335	163	23	in	in	ADP
admet-1335	163	24	figure	figure	NOUN
admet-1335	163	25	4	4	NUM
admet-1335	163	26	.	.	PUNCT
admet-1335	164	1	in	in	ADP
admet-1335	164	2	the	the	DET
admet-1335	164	3	home	home	NOUN
admet-1335	164	4	section	section	NOUN
admet-1335	164	5	,	,	PUNCT
admet-1335	164	6	the	the	DET
admet-1335	164	7	user	user	NOUN
admet-1335	164	8	enters	enter	VERB
admet-1335	164	9	the	the	DET
admet-1335	164	10	protein	protein	NOUN
admet-1335	164	11	sequence	sequence	NOUN
admet-1335	164	12	in	in	ADP
admet-1335	164	13	a	a	DET
admet-1335	164	14	one	one	NUM
admet-1335	164	15	-	-	PUNCT
admet-1335	164	16	letter	letter	NOUN
admet-1335	164	17	code	code	NOUN
admet-1335	164	18	,	,	PUNCT
admet-1335	164	19	and	and	CCONJ
admet-1335	164	20	the	the	DET
admet-1335	164	21	models	model	NOUN
admet-1335	164	22	predict	predict	VERB
admet-1335	164	23	whether	whether	SCONJ
admet-1335	164	24	the	the	DET
admet-1335	164	25	entered	enter	VERB
admet-1335	164	26	sequence	sequence	NOUN
admet-1335	164	27	is	be	AUX
admet-1335	164	28	allergenic	allergenic	ADJ
admet-1335	164	29	or	or	CCONJ
admet-1335	164	30	non	non	ADJ
admet-1335	164	31	-	-	ADJ
admet-1335	164	32	allergenic	allergenic	ADJ
admet-1335	164	33	as	as	SCONJ
admet-1335	164	34	shown	show	VERB
admet-1335	164	35	in	in	ADP
admet-1335	164	36	figure	figure	NOUN
admet-1335	164	37	5	5	NUM
admet-1335	164	38	.	.	PUNCT
admet-1335	165	1	in	in	ADP
admet-1335	165	2	the	the	DET
admet-1335	165	3	dataset	dataset	NOUN
admet-1335	165	4	part	part	NOUN
admet-1335	165	5	,	,	PUNCT
admet-1335	165	6	we	we	PRON
admet-1335	165	7	have	have	AUX
admet-1335	165	8	uploaded	upload	VERB
admet-1335	165	9	the	the	DET
admet-1335	165	10	data	datum	NOUN
admet-1335	165	11	considered	consider	VERB
admet-1335	165	12	in	in	ADP
admet-1335	165	13	our	our	PRON
admet-1335	165	14	research	research	NOUN
admet-1335	165	15	in	in	ADP
admet-1335	165	16	the	the	DET
admet-1335	165	17	fasta	fasta	PROPN
admet-1335	165	18	file	file	NOUN
admet-1335	165	19	format	format	NOUN
admet-1335	165	20	as	as	SCONJ
admet-1335	165	21	represented	represent	VERB
admet-1335	165	22	in	in	ADP
admet-1335	165	23	figure	figure	NOUN
admet-1335	165	24	6	6	NUM
admet-1335	165	25	.	.	PUNCT
admet-1335	166	1	the	the	DET
admet-1335	166	2	method	method	NOUN
admet-1335	166	3	description	description	NOUN
admet-1335	166	4	provides	provide	VERB
admet-1335	166	5	the	the	DET
admet-1335	166	6	user	user	NOUN
admet-1335	166	7	with	with	ADP
admet-1335	166	8	a	a	DET
admet-1335	166	9	brief	brief	ADJ
admet-1335	166	10	description	description	NOUN
admet-1335	166	11	of	of	ADP
admet-1335	166	12	the	the	DET
admet-1335	166	13	methodologies	methodology	NOUN
admet-1335	166	14	we	we	PRON
admet-1335	166	15	have	have	AUX
admet-1335	166	16	considered	consider	VERB
admet-1335	166	17	.	.	PUNCT
admet-1335	167	1	figure	figure	VERB
admet-1335	167	2	4	4	NUM
admet-1335	167	3	.	.	PUNCT
admet-1335	168	1	interface	interface	NOUN
admet-1335	168	2	of	of	ADP
admet-1335	168	3	proall	proall	NOUN
admet-1335	168	4	-	-	PUNCT
admet-1335	168	5	d	d	NOUN
admet-1335	168	6	for	for	ADP
admet-1335	168	7	protein	protein	NOUN
admet-1335	168	8	allergen	allergen	NOUN
admet-1335	168	9	detection	detection	NOUN
admet-1335	168	10	.	.	PUNCT
admet-1335	169	1	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	169	2	pallavi	pallavi	NOUN
admet-1335	169	3	and	and	CCONJ
admet-1335	169	4	rakshitha	rakshitha	PROPN
admet-1335	169	5	admet	admet	PROPN
admet-1335	169	6	&	&	CCONJ
admet-1335	169	7	dmpk	dmpk	PROPN
admet-1335	169	8	10(3	10(3	NUM
admet-1335	169	9	)	)	PUNCT
admet-1335	169	10	(	(	PUNCT
admet-1335	169	11	2022	2022	NUM
admet-1335	169	12	)	)	PUNCT
admet-1335	169	13	231	231	NUM
admet-1335	169	14	-	-	SYM
admet-1335	169	15	240	240	NUM
admet-1335	169	16	238	238	NUM
admet-1335	169	17	figure	figure	NOUN
admet-1335	169	18	5	5	NUM
admet-1335	169	19	.	.	PUNCT
admet-1335	169	20	working	work	VERB
admet-1335	169	21	of	of	ADP
admet-1335	169	22	proall	proall	ADJ
admet-1335	169	23	-	-	PUNCT
admet-1335	169	24	d.	d.	NOUN
admet-1335	169	25	figure	figure	NOUN
admet-1335	169	26	6	6	NUM
admet-1335	169	27	.	.	PUNCT
admet-1335	170	1	data	data	NOUN
admet-1335	170	2	-	-	PUNCT
admet-1335	170	3	set	set	VERB
admet-1335	170	4	section	section	NOUN
admet-1335	170	5	the	the	DET
admet-1335	170	6	supplementary	supplementary	ADJ
admet-1335	170	7	section	section	NOUN
admet-1335	170	8	describes	describe	VERB
admet-1335	170	9	the	the	DET
admet-1335	170	10	detailed	detailed	ADJ
admet-1335	170	11	functioning	functioning	NOUN
admet-1335	170	12	of	of	ADP
admet-1335	170	13	the	the	DET
admet-1335	170	14	web	web	NOUN
admet-1335	170	15	application	application	NOUN
admet-1335	170	16	.	.	PUNCT
admet-1335	171	1	conclusions	conclusion	NOUN
admet-1335	171	2	this	this	DET
admet-1335	171	3	study	study	NOUN
admet-1335	171	4	builds	build	VERB
admet-1335	171	5	on	on	ADP
admet-1335	171	6	and	and	CCONJ
admet-1335	171	7	expands	expand	VERB
admet-1335	171	8	earlier	early	ADJ
admet-1335	171	9	studies	study	NOUN
admet-1335	171	10	to	to	PART
admet-1335	171	11	develop	develop	VERB
admet-1335	171	12	the	the	DET
admet-1335	171	13	analysis	analysis	NOUN
admet-1335	171	14	of	of	ADP
admet-1335	171	15	potential	potential	ADJ
admet-1335	171	16	protein	protein	NOUN
admet-1335	171	17	allergens	allergen	NOUN
admet-1335	171	18	.	.	PUNCT
admet-1335	172	1	our	our	PRON
admet-1335	172	2	first	first	ADJ
admet-1335	172	3	aim	aim	NOUN
admet-1335	172	4	has	have	AUX
admet-1335	172	5	been	be	AUX
admet-1335	172	6	to	to	PART
admet-1335	172	7	update	update	VERB
admet-1335	172	8	the	the	DET
admet-1335	172	9	technique	technique	NOUN
admet-1335	172	10	while	while	SCONJ
admet-1335	172	11	keeping	keep	VERB
admet-1335	172	12	the	the	DET
admet-1335	172	13	previous	previous	ADJ
admet-1335	172	14	factors	factor	NOUN
admet-1335	172	15	in	in	ADP
admet-1335	172	16	mind	mind	NOUN
admet-1335	172	17	.	.	PUNCT
admet-1335	173	1	we	we	PRON
admet-1335	173	2	evaluated	evaluate	VERB
admet-1335	173	3	deep	deep	ADJ
admet-1335	173	4	learning	learning	NOUN
admet-1335	173	5	,	,	PUNCT
admet-1335	173	6	ensemble	ensemble	ADJ
admet-1335	173	7	learning	learning	NOUN
admet-1335	173	8	,	,	PUNCT
admet-1335	173	9	and	and	CCONJ
admet-1335	173	10	machine	machine	NOUN
admet-1335	173	11	learning	learning	NOUN
admet-1335	173	12	models	model	NOUN
admet-1335	173	13	such	such	ADJ
admet-1335	173	14	as	as	ADP
admet-1335	173	15	the	the	DET
admet-1335	173	16	gaussian	gaussian	ADJ
admet-1335	173	17	naive	naive	ADJ
admet-1335	173	18	bayes	bayes	NOUN
admet-1335	173	19	,	,	PUNCT
admet-1335	173	20	radius	radius	NOUN
admet-1335	173	21	neighbour	neighbour	NOUN
admet-1335	173	22	’s	’s	PART
admet-1335	173	23	classifier	classifier	NOUN
admet-1335	173	24	,	,	PUNCT
admet-1335	173	25	bagging	bagging	NOUN
admet-1335	173	26	classifier	classifier	NOUN
admet-1335	173	27	,	,	PUNCT
admet-1335	173	28	ada	ada	PROPN
admet-1335	173	29	boost	boost	PROPN
admet-1335	173	30	,	,	PUNCT
admet-1335	173	31	linear	linear	ADJ
admet-1335	173	32	discriminant	discriminant	ADJ
admet-1335	173	33	analysis	analysis	NOUN
admet-1335	173	34	,	,	PUNCT
admet-1335	173	35	quadratic	quadratic	ADJ
admet-1335	173	36	discriminant	discriminant	ADJ
admet-1335	173	37	analysis	analysis	NOUN
admet-1335	173	38	,	,	PUNCT
admet-1335	173	39	and	and	CCONJ
admet-1335	173	40	lstm	lstm	NOUN
admet-1335	173	41	to	to	PART
admet-1335	173	42	predict	predict	VERB
admet-1335	173	43	the	the	DET
admet-1335	173	44	allergenicity	allergenicity	NOUN
admet-1335	173	45	of	of	ADP
admet-1335	173	46	proteins	protein	NOUN
admet-1335	173	47	.	.	PUNCT
admet-1335	174	1	extensive	extensive	ADJ
admet-1335	174	2	testing	testing	NOUN
admet-1335	174	3	produced	produce	VERB
admet-1335	174	4	excellent	excellent	ADJ
admet-1335	174	5	results	result	NOUN
admet-1335	174	6	.	.	PUNCT
admet-1335	175	1	they	they	PRON
admet-1335	175	2	admet	admet	PROPN
admet-1335	175	3	&	&	CCONJ
admet-1335	175	4	dmpk	dmpk	PROPN
admet-1335	175	5	10(3	10(3	NUM
admet-1335	175	6	)	)	PUNCT
admet-1335	175	7	(	(	PUNCT
admet-1335	175	8	2022	2022	NUM
admet-1335	175	9	)	)	PUNCT
admet-1335	175	10	231	231	NUM
admet-1335	175	11	-	-	SYM
admet-1335	175	12	240	240	NUM
admet-1335	175	13	proall	proall	NOUN
admet-1335	175	14	-	-	PUNCT
admet-1335	175	15	d	d	NOUN
admet-1335	175	16	:	:	PUNCT
admet-1335	175	17	protein	protein	NOUN
admet-1335	175	18	allergen	allergen	NOUN
admet-1335	175	19	detection	detection	NOUN
admet-1335	175	20	doi	doi	NOUN
admet-1335	175	21	:	:	PUNCT
admet-1335	175	22	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	175	23	239	239	NUM
admet-1335	175	24	were	be	AUX
admet-1335	175	25	superior	superior	ADJ
admet-1335	175	26	and	and	CCONJ
admet-1335	175	27	corroborated	corroborated	ADJ
admet-1335	175	28	earlier	early	ADJ
admet-1335	175	29	research	research	NOUN
admet-1335	175	30	.	.	PUNCT
admet-1335	176	1	furthermore	furthermore	ADV
admet-1335	176	2	,	,	PUNCT
admet-1335	176	3	the	the	DET
admet-1335	176	4	auc	auc	NOUN
admet-1335	176	5	value	value	NOUN
admet-1335	176	6	of	of	ADP
admet-1335	176	7	lstm	lstm	NOUN
admet-1335	176	8	(	(	PUNCT
admet-1335	176	9	the	the	DET
admet-1335	176	10	best	good	ADJ
admet-1335	176	11	performance	performance	NOUN
admet-1335	176	12	)	)	PUNCT
admet-1335	176	13	was	be	AUX
admet-1335	176	14	0.9152	0.9152	NUM
admet-1335	176	15	.	.	PUNCT
admet-1335	177	1	so	so	ADV
admet-1335	177	2	far	far	ADV
admet-1335	177	3	,	,	PUNCT
admet-1335	177	4	this	this	PRON
admet-1335	177	5	is	be	AUX
admet-1335	177	6	the	the	DET
admet-1335	177	7	only	only	ADJ
admet-1335	177	8	study	study	NOUN
admet-1335	177	9	to	to	PART
admet-1335	177	10	apply	apply	VERB
admet-1335	177	11	the	the	DET
admet-1335	177	12	aforementioned	aforementioned	ADJ
admet-1335	177	13	methods	method	NOUN
admet-1335	177	14	to	to	PART
admet-1335	177	15	evaluate	evaluate	VERB
admet-1335	177	16	protein	protein	NOUN
admet-1335	177	17	allergenicity	allergenicity	NOUN
admet-1335	177	18	,	,	PUNCT
admet-1335	177	19	and	and	CCONJ
admet-1335	177	20	it	it	PRON
admet-1335	177	21	will	will	AUX
admet-1335	177	22	serve	serve	VERB
admet-1335	177	23	as	as	ADP
admet-1335	177	24	a	a	DET
admet-1335	177	25	paradigm	paradigm	NOUN
admet-1335	177	26	for	for	ADP
admet-1335	177	27	future	future	ADJ
admet-1335	177	28	protein	protein	NOUN
admet-1335	177	29	allergen	allergen	NOUN
admet-1335	177	30	prediction	prediction	NOUN
admet-1335	177	31	.	.	PUNCT
admet-1335	178	1	conflict	conflict	NOUN
admet-1335	178	2	of	of	ADP
admet-1335	178	3	interest	interest	NOUN
admet-1335	178	4	:	:	PUNCT
admet-1335	178	5	all	all	DET
admet-1335	178	6	the	the	DET
admet-1335	178	7	authors	author	NOUN
admet-1335	178	8	declare	declare	VERB
admet-1335	178	9	no	no	DET
admet-1335	178	10	conflict	conflict	NOUN
admet-1335	178	11	of	of	ADP
admet-1335	178	12	interest	interest	NOUN
admet-1335	178	13	.	.	PUNCT
admet-1335	179	1	references	reference	NOUN
admet-1335	179	2	[	[	X
admet-1335	179	3	1	1	NUM
admet-1335	179	4	]	]	X
admet-1335	179	5	m.b	m.b	PROPN
admet-1335	179	6	.	.	PROPN
admet-1335	179	7	stadler	stadler	PROPN
admet-1335	179	8	,	,	PUNCT
admet-1335	179	9	b.m	b.m	PROPN
admet-1335	179	10	.	.	PROPN
admet-1335	179	11	stadler	stadler	PROPN
admet-1335	179	12	.	.	PUNCT
admet-1335	180	1	allergenicity	allergenicity	NOUN
admet-1335	180	2	prediction	prediction	NOUN
admet-1335	180	3	by	by	ADP
admet-1335	180	4	protein	protein	NOUN
admet-1335	180	5	sequence	sequence	NOUN
admet-1335	180	6	.	.	PUNCT
admet-1335	181	1	faseb	faseb	PROPN
admet-1335	181	2	j.	j.	PROPN
admet-1335	181	3	17	17	NUM
admet-1335	181	4	(	(	PUNCT
admet-1335	181	5	2003	2003	NUM
admet-1335	181	6	)	)	PUNCT
admet-1335	181	7	1141	1141	NUM
admet-1335	181	8	.	.	PUNCT
admet-1335	182	1	https://doi:10.1096	https://doi:10.1096	NOUN
admet-1335	182	2	/	/	SYM
admet-1335	182	3	fj.02	fj.02	PROPN
admet-1335	182	4	-	-	PUNCT
admet-1335	182	5	1052fje	1052fje	NOUN
admet-1335	182	6	.	.	PUNCT
admet-1335	183	1	[	[	X
admet-1335	183	2	2	2	NUM
admet-1335	183	3	]	]	X
admet-1335	183	4	r.e	r.e	PROPN
admet-1335	183	5	.	.	PROPN
admet-1335	183	6	poms	poms	PROPN
admet-1335	183	7	,	,	PUNCT
admet-1335	183	8	e.	e.	PROPN
admet-1335	183	9	anklam	anklam	PROPN
admet-1335	183	10	,	,	PUNCT
admet-1335	183	11	m.	m.	NOUN
admet-1335	183	12	akuhn	akuhn	NOUN
admet-1335	183	13	.	.	PUNCT
admet-1335	184	1	polymerase	polymerase	NOUN
admet-1335	184	2	chain	chain	NOUN
admet-1335	184	3	reaction	reaction	NOUN
admet-1335	184	4	techniques	technique	NOUN
admet-1335	184	5	for	for	ADP
admet-1335	184	6	food	food	NOUN
admet-1335	184	7	allergen	allergen	NOUN
admet-1335	184	8	detection	detection	NOUN
admet-1335	184	9	.	.	PUNCT
admet-1335	185	1	journal	journal	PROPN
admet-1335	185	2	of	of	ADP
admet-1335	185	3	aoac	aoac	ADJ
admet-1335	185	4	international	international	ADJ
admet-1335	185	5	87	87	NUM
admet-1335	185	6	(	(	PUNCT
admet-1335	185	7	2004	2004	NUM
admet-1335	185	8	)	)	PUNCT
admet-1335	185	9	1391	1391	NUM
admet-1335	185	10	-	-	SYM
admet-1335	185	11	1397	1397	NUM
admet-1335	185	12	.	.	PUNCT
admet-1335	186	1	https://doi.org/10.1093/jaoac/87.6.1391	https://doi.org/10.1093/jaoac/87.6.1391	PROPN
admet-1335	186	2	.	.	PUNCT
admet-1335	187	1	[	[	X
admet-1335	187	2	3	3	X
admet-1335	187	3	]	]	X
admet-1335	187	4	s.	s.	PROPN
admet-1335	187	5	saha	saha	PROPN
admet-1335	187	6	,	,	PUNCT
admet-1335	187	7	g.s	g.s	PROPN
admet-1335	187	8	.	.	PROPN
admet-1335	187	9	raghava	raghava	PROPN
admet-1335	187	10	.	.	PROPN
admet-1335	187	11	algpred	algpre	VERB
admet-1335	187	12	:	:	PUNCT
admet-1335	187	13	prediction	prediction	NOUN
admet-1335	187	14	of	of	ADP
admet-1335	187	15	allergenic	allergenic	ADJ
admet-1335	187	16	proteins	protein	NOUN
admet-1335	187	17	and	and	CCONJ
admet-1335	187	18	mapping	mapping	NOUN
admet-1335	187	19	of	of	ADP
admet-1335	187	20	ige	ige	PROPN
admet-1335	187	21	epitopes	epitope	NOUN
admet-1335	187	22	.	.	PUNCT
admet-1335	188	1	nucleic	nucleic	ADJ
admet-1335	188	2	acids	acid	NOUN
admet-1335	188	3	research	research	NOUN
admet-1335	188	4	34	34	NUM
admet-1335	188	5	(	(	PUNCT
admet-1335	188	6	2006	2006	NUM
admet-1335	188	7	)	)	PUNCT
admet-1335	189	1	w202	w202	PROPN
admet-1335	189	2	-	-	PUNCT
admet-1335	189	3	w209	w209	PROPN
admet-1335	189	4	.	.	PUNCT
admet-1335	189	5	https://doi.org/10.1093/nar/gkl343	https://doi.org/10.1093/nar/gkl343	PROPN
admet-1335	189	6	.	.	PUNCT
admet-1335	190	1	[	[	X
admet-1335	190	2	4	4	X
admet-1335	190	3	]	]	X
admet-1335	190	4	h.c	h.c	PROPN
admet-1335	190	5	.	.	PUNCT
admet-1335	190	6	muh	muh	PROPN
admet-1335	190	7	,	,	PUNCT
admet-1335	190	8	j.c	j.c	PROPN
admet-1335	190	9	.	.	PROPN
admet-1335	190	10	tong	tong	PROPN
admet-1335	190	11	.	.	PUNCT
admet-1335	191	1	allerhunter	allerhunter	NOUN
admet-1335	191	2	:	:	PUNCT
admet-1335	191	3	a	a	DET
admet-1335	191	4	svm	svm	ADJ
admet-1335	191	5	-	-	PUNCT
admet-1335	191	6	pairwise	pairwise	NOUN
admet-1335	191	7	system	system	NOUN
admet-1335	191	8	for	for	ADP
admet-1335	191	9	assessment	assessment	NOUN
admet-1335	191	10	of	of	ADP
admet-1335	191	11	allergenicity	allergenicity	NOUN
admet-1335	191	12	and	and	CCONJ
admet-1335	191	13	allergic	allergic	ADJ
admet-1335	191	14	cross	cross	NOUN
admet-1335	191	15	-	-	NOUN
admet-1335	191	16	reactivity	reactivity	NOUN
admet-1335	191	17	in	in	ADP
admet-1335	191	18	proteins	protein	NOUN
admet-1335	191	19	.	.	PUNCT
admet-1335	192	1	plos	plos	PROPN
admet-1335	192	2	one	one	NUM
admet-1335	192	3	4	4	NUM
admet-1335	192	4	(	(	PUNCT
admet-1335	192	5	2009	2009	NUM
admet-1335	192	6	)	)	PUNCT
admet-1335	192	7	e5861	e5861	PROPN
admet-1335	192	8	.	.	PUNCT
admet-1335	192	9	https://doi.org/10.1371/journal.pone.0005861	https://doi.org/10.1371/journal.pone.0005861	PROPN
admet-1335	192	10	.	.	PUNCT
admet-1335	193	1	[	[	X
admet-1335	193	2	5	5	X
admet-1335	193	3	]	]	PUNCT
admet-1335	193	4	h.	h.	PROPN
admet-1335	193	5	mohabatkar	mohabatkar	PROPN
admet-1335	193	6	,	,	PUNCT
admet-1335	193	7	b.m	b.m	PROPN
admet-1335	193	8	.	.	PROPN
admet-1335	193	9	mohammad	mohammad	PROPN
admet-1335	193	10	,	,	PUNCT
admet-1335	193	11	k.	k.	PROPN
admet-1335	193	12	abdolahi	abdolahi	PROPN
admet-1335	193	13	,	,	PUNCT
admet-1335	193	14	s.	s.	PROPN
admet-1335	193	15	mohsenzadeh	mohsenzadeh	PROPN
admet-1335	193	16	.	.	PUNCT
admet-1335	194	1	prediction	prediction	NOUN
admet-1335	194	2	of	of	ADP
admet-1335	194	3	allergenic	allergenic	ADJ
admet-1335	194	4	proteins	protein	NOUN
admet-1335	194	5	by	by	ADP
admet-1335	194	6	means	mean	NOUN
admet-1335	194	7	of	of	ADP
admet-1335	194	8	the	the	DET
admet-1335	194	9	concept	concept	NOUN
admet-1335	194	10	of	of	ADP
admet-1335	194	11	chou	chou	NOUN
admet-1335	194	12	's	's	PART
admet-1335	194	13	pseudo	pseudo	NOUN
admet-1335	194	14	amino	amino	NOUN
admet-1335	194	15	acid	acid	NOUN
admet-1335	194	16	composition	composition	NOUN
admet-1335	194	17	and	and	CCONJ
admet-1335	194	18	a	a	DET
admet-1335	194	19	machine	machine	NOUN
admet-1335	194	20	learning	learn	VERB
admet-1335	194	21	approach	approach	NOUN
admet-1335	194	22	.	.	PUNCT
admet-1335	195	1	medicinal	medicinal	ADJ
admet-1335	195	2	chemistry	chemistry	NOUN
admet-1335	195	3	9	9	NUM
admet-1335	195	4	(	(	PUNCT
admet-1335	195	5	2013	2013	NUM
admet-1335	195	6	)	)	PUNCT
admet-1335	195	7	133	133	NUM
admet-1335	195	8	-	-	SYM
admet-1335	195	9	137	137	NUM
admet-1335	195	10	.	.	PUNCT
admet-1335	196	1	https://doi.org/10.2174/157340613804488341	https://doi.org/10.2174/157340613804488341	NOUN
admet-1335	196	2	.	.	PUNCT
admet-1335	197	1	[	[	X
admet-1335	197	2	6	6	NUM
admet-1335	197	3	]	]	PUNCT
admet-1335	197	4	s.	s.	PROPN
admet-1335	197	5	vijayakumar	vijayakumar	PROPN
admet-1335	197	6	,	,	PUNCT
admet-1335	197	7	p.t.v	p.t.v	PROPN
admet-1335	197	8	.	.	PUNCT
admet-1335	197	9	lakshmi	lakshmi	PROPN
admet-1335	197	10	.	.	PUNCT
admet-1335	198	1	ieee	ieee	PROPN
admet-1335	198	2	international	international	PROPN
admet-1335	198	3	conference	conference	NOUN
admet-1335	198	4	on	on	ADP
admet-1335	198	5	bioinformatics	bioinformatics	NOUN
admet-1335	198	6	and	and	CCONJ
admet-1335	198	7	biomedicine	biomedicine	NOUN
admet-1335	198	8	,	,	PUNCT
admet-1335	198	9	a	a	DET
admet-1335	198	10	fuzzy	fuzzy	ADJ
admet-1335	198	11	inference	inference	NOUN
admet-1335	198	12	system	system	NOUN
admet-1335	198	13	for	for	ADP
admet-1335	198	14	predicting	predict	VERB
admet-1335	198	15	allergenicity	allergenicity	NOUN
admet-1335	198	16	and	and	CCONJ
admet-1335	198	17	allergic	allergic	ADJ
admet-1335	198	18	cross	cross	NOUN
admet-1335	198	19	-	-	NOUN
admet-1335	198	20	reactivity	reactivity	NOUN
admet-1335	198	21	in	in	ADP
admet-1335	198	22	proteins	protein	NOUN
admet-1335	198	23	,	,	PUNCT
admet-1335	198	24	tongji	tongji	PROPN
admet-1335	198	25	university	university	PROPN
admet-1335	198	26	,	,	PUNCT
admet-1335	198	27	china	china	PROPN
admet-1335	198	28	.	.	PUNCT
admet-1335	199	1	(	(	PUNCT
admet-1335	199	2	2013	2013	NUM
admet-1335	199	3	)	)	PUNCT
admet-1335	199	4	49	49	NUM
admet-1335	199	5	-	-	SYM
admet-1335	199	6	52	52	NUM
admet-1335	199	7	.	.	PUNCT
admet-1335	200	1	https://doi.org/10.1109/bibm.2013.6732458	https://doi.org/10.1109/bibm.2013.6732458	PROPN
admet-1335	200	2	.	.	PUNCT
admet-1335	201	1	[	[	X
admet-1335	201	2	7	7	NUM
admet-1335	201	3	]	]	X
admet-1335	201	4	i.	i.	NOUN
admet-1335	201	5	dimitrov	dimitrov	PROPN
admet-1335	201	6	,	,	PUNCT
admet-1335	201	7	d.r	d.r	PROPN
admet-1335	201	8	.	.	PROPN
admet-1335	201	9	flower	flower	PROPN
admet-1335	201	10	,	,	PUNCT
admet-1335	201	11	i.	i.	PROPN
admet-1335	201	12	doytchinova	doytchinova	PROPN
admet-1335	201	13	.	.	PUNCT
admet-1335	202	1	bmc	bmc	PROPN
admet-1335	202	2	bioinformatics	bioinformatics	PROPN
admet-1335	202	3	,	,	PUNCT
admet-1335	202	4	allertop	allertop	VERB
admet-1335	202	5	–	–	PUNCT
admet-1335	202	6	a	a	DET
admet-1335	202	7	server	server	NOUN
admet-1335	202	8	for	for	ADP
admet-1335	202	9	in	in	ADP
admet-1335	202	10	silico	silico	NOUN
admet-1335	202	11	prediction	prediction	NOUN
admet-1335	202	12	of	of	ADP
admet-1335	202	13	allergens	allergen	NOUN
admet-1335	202	14	,	,	PUNCT
admet-1335	202	15	cambridge	cambridge	PROPN
admet-1335	202	16	,	,	PUNCT
admet-1335	202	17	uk	uk	PROPN
admet-1335	202	18	,	,	PUNCT
admet-1335	202	19	2013	2013	NUM
admet-1335	202	20	,	,	PUNCT
admet-1335	202	21	1	1	NUM
admet-1335	202	22	-	-	SYM
admet-1335	202	23	9	9	NUM
admet-1335	202	24	.	.	PUNCT
admet-1335	203	1	https://doi.org/10.1186/1471-2105-14-s6-s4	https://doi.org/10.1186/1471-2105-14-s6-s4	VERB
admet-1335	203	2	.	.	PUNCT
admet-1335	204	1	[	[	X
admet-1335	204	2	8	8	NUM
admet-1335	204	3	]	]	X
admet-1335	204	4	i.	i.	NOUN
admet-1335	204	5	dimitrov	dimitrov	PROPN
admet-1335	204	6	,	,	PUNCT
admet-1335	204	7	l.	l.	PROPN
admet-1335	204	8	naneva	naneva	PROPN
admet-1335	204	9	,	,	PUNCT
admet-1335	204	10	i.	i.	PROPN
admet-1335	204	11	doytchinova	doytchinova	PROPN
admet-1335	204	12	,	,	PUNCT
admet-1335	204	13	i.	i.	PROPN
admet-1335	204	14	bangov	bangov	PROPN
admet-1335	204	15	.	.	PUNCT
admet-1335	205	1	allergenfp	allergenfp	NOUN
admet-1335	205	2	:	:	PUNCT
admet-1335	205	3	allergenicity	allergenicity	NOUN
admet-1335	205	4	prediction	prediction	NOUN
admet-1335	205	5	by	by	ADP
admet-1335	205	6	descriptor	descriptor	NOUN
admet-1335	205	7	fingerprints	fingerprint	NOUN
admet-1335	205	8	.	.	PUNCT
admet-1335	206	1	bioinformatics	bioinformatic	NOUN
admet-1335	206	2	30	30	NUM
admet-1335	206	3	(	(	PUNCT
admet-1335	206	4	2014	2014	NUM
admet-1335	206	5	)	)	PUNCT
admet-1335	206	6	846	846	NUM
admet-1335	206	7	-	-	SYM
admet-1335	206	8	851	851	NUM
admet-1335	206	9	.	.	PUNCT
admet-1335	207	1	https://doi.org/10.1093/bioinformatics/btt619	https://doi.org/10.1093/bioinformatics/btt619	PRON
admet-1335	207	2	.	.	PUNCT
admet-1335	208	1	[	[	X
admet-1335	208	2	9	9	NUM
admet-1335	208	3	]	]	PUNCT
admet-1335	208	4	i.	i.	NOUN
admet-1335	208	5	dimitrov	dimitrov	PROPN
admet-1335	208	6	,	,	PUNCT
admet-1335	208	7	l.	l.	PROPN
admet-1335	208	8	naneva	naneva	PROPN
admet-1335	208	9	,	,	PUNCT
admet-1335	208	10	i.	i.	PROPN
admet-1335	208	11	bangov	bangov	PROPN
admet-1335	208	12	,	,	PUNCT
admet-1335	208	13	i.	i.	PROPN
admet-1335	208	14	doytchinova	doytchinova	PROPN
admet-1335	208	15	.	.	PUNCT
admet-1335	208	16	allergenicity	allergenicity	NOUN
admet-1335	208	17	prediction	prediction	NOUN
admet-1335	208	18	by	by	ADP
admet-1335	208	19	artificial	artificial	ADJ
admet-1335	208	20	neural	neural	ADJ
admet-1335	208	21	networks	network	NOUN
admet-1335	208	22	.	.	PUNCT
admet-1335	209	1	journal	journal	PROPN
admet-1335	209	2	of	of	ADP
admet-1335	209	3	chemometrics	chemometric	NOUN
admet-1335	209	4	28	28	NUM
admet-1335	209	5	(	(	PUNCT
admet-1335	209	6	2014	2014	NUM
admet-1335	209	7	)	)	PUNCT
admet-1335	209	8	282	282	NUM
admet-1335	209	9	-	-	SYM
admet-1335	209	10	286	286	NUM
admet-1335	209	11	.	.	PUNCT
admet-1335	210	1	https://doi.org/10.1002/cem.2597	https://doi.org/10.1002/cem.2597	NOUN
admet-1335	210	2	.	.	PUNCT
admet-1335	211	1	[	[	X
admet-1335	211	2	10	10	NUM
admet-1335	211	3	]	]	X
admet-1335	211	4	i.	i.	NOUN
admet-1335	211	5	dimitrov	dimitrov	PROPN
admet-1335	211	6	,	,	PUNCT
admet-1335	211	7	i.	i.	PROPN
admet-1335	211	8	bangov	bangov	PROPN
admet-1335	211	9	,	,	PUNCT
admet-1335	211	10	d.r	d.r	PROPN
admet-1335	211	11	.	.	PROPN
admet-1335	211	12	flower	flower	PROPN
admet-1335	211	13	,	,	PUNCT
admet-1335	211	14	i.	i.	PROPN
admet-1335	211	15	doytchinova	doytchinova	PROPN
admet-1335	211	16	.	.	PUNCT
admet-1335	212	1	allertop	allertop	PROPN
admet-1335	212	2	v.2	v.2	NOUN
admet-1335	212	3	–	–	PUNCT
admet-1335	212	4	a	a	DET
admet-1335	212	5	server	server	NOUN
admet-1335	212	6	for	for	ADP
admet-1335	212	7	in	in	ADP
admet-1335	212	8	silico	silico	NOUN
admet-1335	212	9	prediction	prediction	NOUN
admet-1335	212	10	of	of	ADP
admet-1335	212	11	allergens	allergen	NOUN
admet-1335	212	12	.	.	PUNCT
admet-1335	213	1	journal	journal	NOUN
admet-1335	213	2	of	of	ADP
admet-1335	213	3	molecular	molecular	ADJ
admet-1335	213	4	modelling	modelling	NOUN
admet-1335	213	5	20	20	NUM
admet-1335	213	6	(	(	PUNCT
admet-1335	213	7	2014	2014	NUM
admet-1335	213	8	)	)	PUNCT
admet-1335	213	9	1	1	NUM
admet-1335	213	10	-	-	SYM
admet-1335	213	11	6	6	NUM
admet-1335	213	12	.	.	PUNCT
admet-1335	214	1	https://doi.org/10.1007/s00894-014-2278-5	https://doi.org/10.1007/s00894-014-2278-5	PROPN
admet-1335	214	2	.	.	PUNCT
admet-1335	215	1	[	[	X
admet-1335	215	2	11	11	NUM
admet-1335	215	3	]	]	X
admet-1335	215	4	ha	ha	INTJ
admet-1335	215	5	.	.	PUNCT
admet-1335	215	6	x.	x.	PROPN
admet-1335	215	7	dang	dang	PROPN
admet-1335	215	8	,	,	PUNCT
admet-1335	215	9	c.b	c.b	PROPN
admet-1335	215	10	.	.	PROPN
admet-1335	215	11	lawrence	lawrence	PROPN
admet-1335	215	12	.	.	PROPN
admet-1335	215	13	allerdictor	allerdictor	PROPN
admet-1335	215	14	:	:	PUNCT
admet-1335	215	15	fast	fast	ADJ
admet-1335	215	16	allergen	allergen	NOUN
admet-1335	215	17	prediction	prediction	NOUN
admet-1335	215	18	using	use	VERB
admet-1335	215	19	text	text	NOUN
admet-1335	215	20	classification	classification	NOUN
admet-1335	215	21	techniques	technique	NOUN
admet-1335	215	22	.	.	PUNCT
admet-1335	216	1	bioinformatics	bioinformatic	NOUN
admet-1335	216	2	30	30	NUM
admet-1335	216	3	(	(	PUNCT
admet-1335	216	4	2014	2014	NUM
admet-1335	216	5	)	)	PUNCT
admet-1335	216	6	1120	1120	NUM
admet-1335	216	7	-	-	SYM
admet-1335	216	8	1128	1128	NUM
admet-1335	216	9	.	.	PUNCT
admet-1335	217	1	https://doi.org/10.1093/bioinformatics/btu004	https://doi.org/10.1093/bioinformatics/btu004	NOUN
admet-1335	217	2	.	.	PUNCT
admet-1335	218	1	[	[	X
admet-1335	218	2	12	12	NUM
admet-1335	218	3	]	]	X
admet-1335	218	4	s.s	s.s	PROPN
admet-1335	218	5	.	.	PROPN
admet-1335	218	6	negi	negi	PROPN
admet-1335	218	7	,	,	PUNCT
admet-1335	218	8	w.	w.	PROPN
admet-1335	218	9	braun	braun	PROPN
admet-1335	218	10	.	.	PUNCT
admet-1335	219	1	cross	cross	ADJ
admet-1335	219	2	-	-	ADJ
admet-1335	219	3	react	react	ADJ
admet-1335	219	4	:	:	PUNCT
admet-1335	219	5	a	a	DET
admet-1335	219	6	new	new	ADJ
admet-1335	219	7	structural	structural	ADJ
admet-1335	219	8	bioinformatics	bioinformatics	NOUN
admet-1335	219	9	method	method	NOUN
admet-1335	219	10	for	for	ADP
admet-1335	219	11	predicting	predict	VERB
admet-1335	219	12	allergen	allergen	NOUN
admet-1335	219	13	crossreactivity	crossreactivity	NOUN
admet-1335	219	14	.	.	PUNCT
admet-1335	220	1	bioinformatics	bioinformatic	NOUN
admet-1335	220	2	33	33	NUM
admet-1335	220	3	(	(	PUNCT
admet-1335	220	4	2017	2017	NUM
admet-1335	220	5	)	)	PUNCT
admet-1335	220	6	1014	1014	NUM
admet-1335	220	7	-	-	SYM
admet-1335	220	8	1020	1020	NUM
admet-1335	220	9	.	.	PUNCT
admet-1335	221	1	https://doi.org/10.1093/bioinformatics/btw767	https://doi.org/10.1093/bioinformatics/btw767	NOUN
admet-1335	221	2	.	.	PUNCT
admet-1335	222	1	[	[	X
admet-1335	222	2	13	13	NUM
admet-1335	222	3	]	]	X
admet-1335	222	4	g.s	g.s	PROPN
admet-1335	222	5	.	.	PROPN
admet-1335	222	6	ladics	ladics	PROPN
admet-1335	222	7	.	.	PUNCT
admet-1335	223	1	assessment	assessment	NOUN
admet-1335	223	2	of	of	ADP
admet-1335	223	3	the	the	DET
admet-1335	223	4	potential	potential	ADJ
admet-1335	223	5	allergenicity	allergenicity	NOUN
admet-1335	223	6	of	of	ADP
admet-1335	223	7	genetically	genetically	ADV
admet-1335	223	8	-	-	PUNCT
admet-1335	223	9	engineered	engineer	VERB
admet-1335	223	10	food	food	NOUN
admet-1335	223	11	crops	crop	NOUN
admet-1335	223	12	.	.	PUNCT
admet-1335	224	1	journal	journal	NOUN
admet-1335	224	2	of	of	ADP
admet-1335	224	3	immunotoxicology	immunotoxicology	NOUN
admet-1335	224	4	16	16	NUM
admet-1335	224	5	(	(	PUNCT
admet-1335	224	6	2019	2019	NUM
admet-1335	224	7	)	)	PUNCT
admet-1335	224	8	43	43	NUM
admet-1335	224	9	-	-	SYM
admet-1335	224	10	53	53	NUM
admet-1335	224	11	.	.	PUNCT
admet-1335	225	1	https://doi.org/10.1080/1547691x.2018.1533904	https://doi.org/10.1080/1547691x.2018.1533904	PROPN
admet-1335	225	2	.	.	PUNCT
admet-1335	226	1	[	[	X
admet-1335	226	2	14	14	NUM
admet-1335	226	3	]	]	X
admet-1335	226	4	s.	s.	PROPN
admet-1335	226	5	maurer	maurer	PROPN
admet-1335	226	6	-	-	PUNCT
admet-1335	226	7	stroh	stroh	PROPN
admet-1335	226	8	,	,	PUNCT
admet-1335	226	9	n.l	n.l	PROPN
admet-1335	226	10	.	.	PROPN
admet-1335	226	11	krutz	krutz	PROPN
admet-1335	226	12	,	,	PUNCT
admet-1335	226	13	p.s	p.s	PROPN
admet-1335	226	14	.	.	PROPN
admet-1335	226	15	kern	kern	PROPN
admet-1335	226	16	,	,	PUNCT
admet-1335	226	17	v.	v.	ADP
admet-1335	226	18	gunalan	gunalan	PROPN
admet-1335	226	19	,	,	PUNCT
admet-1335	226	20	m.n	m.n	PROPN
admet-1335	226	21	.	.	PROPN
admet-1335	226	22	nguyen	nguyen	PROPN
admet-1335	226	23	,	,	PUNCT
admet-1335	226	24	v.	v.	ADP
admet-1335	226	25	limviphuvadh	limviphuvadh	PROPN
admet-1335	226	26	,	,	PUNCT
admet-1335	226	27	f.	f.	PROPN
admet-1335	226	28	eisenhaber	eisenhaber	PROPN
admet-1335	226	29	,	,	PUNCT
admet-1335	226	30	g.f	g.f	PROPN
admet-1335	226	31	.	.	PROPN
admet-1335	226	32	gerberick	gerberick	PROPN
admet-1335	226	33	.	.	PUNCT
admet-1335	227	1	allercatpro	allercatpro	ADJ
admet-1335	227	2	-	-	PUNCT
admet-1335	227	3	prediction	prediction	NOUN
admet-1335	227	4	of	of	ADP
admet-1335	227	5	protein	protein	NOUN
admet-1335	227	6	allergenicity	allergenicity	NOUN
admet-1335	227	7	potential	potential	NOUN
admet-1335	227	8	from	from	ADP
admet-1335	227	9	the	the	DET
admet-1335	227	10	protein	protein	NOUN
admet-1335	227	11	sequence	sequence	NOUN
admet-1335	227	12	.	.	PUNCT
admet-1335	228	1	bioinformatics	bioinformatic	NOUN
admet-1335	228	2	35	35	NUM
admet-1335	228	3	(	(	PUNCT
admet-1335	228	4	2019	2019	NUM
admet-1335	228	5	)	)	PUNCT
admet-1335	228	6	3020	3020	NUM
admet-1335	228	7	-	-	SYM
admet-1335	228	8	3027	3027	NUM
admet-1335	228	9	.	.	PUNCT
admet-1335	229	1	https://doi.org/10.1093/bioinformatics/btz029	https://doi.org/10.1093/bioinformatics/btz029	NOUN
admet-1335	229	2	.	.	PUNCT
admet-1335	230	1	[	[	X
admet-1335	230	2	15	15	NUM
admet-1335	230	3	]	]	X
admet-1335	230	4	m.s	m.s	PROPN
admet-1335	230	5	.	.	PROPN
admet-1335	230	6	pallavi	pallavi	PROPN
admet-1335	230	7	,	,	PUNCT
admet-1335	230	8	h.s	h.s	PROPN
admet-1335	230	9	.	.	PROPN
admet-1335	230	10	pramod	pramod	PROPN
admet-1335	230	11	kumar	kumar	PROPN
admet-1335	230	12	.	.	PROPN
admet-1335	231	1	in	in	ADP
admet-1335	231	2	-	-	PUNCT
admet-1335	231	3	silico	silico	NOUN
admet-1335	231	4	analysis	analysis	NOUN
admet-1335	231	5	to	to	PART
admet-1335	231	6	determine	determine	VERB
admet-1335	231	7	the	the	DET
admet-1335	231	8	efficient	efficient	ADJ
admet-1335	231	9	drug	drug	NOUN
admet-1335	231	10	for	for	ADP
admet-1335	231	11	malignant	malignant	ADJ
admet-1335	231	12	melanoma	melanoma	NOUN
admet-1335	231	13	using	use	VERB
admet-1335	231	14	molecular	molecular	ADJ
admet-1335	231	15	dynamics	dynamic	NOUN
admet-1335	231	16	.	.	PUNCT
admet-1335	232	1	biomedical	biomedical	ADJ
admet-1335	232	2	and	and	CCONJ
admet-1335	232	3	pharmacology	pharmacology	NOUN
admet-1335	232	4	journal	journal	NOUN
admet-1335	232	5	13	13	NUM
admet-1335	232	6	(	(	PUNCT
admet-1335	232	7	2020	2020	NUM
admet-1335	232	8	)	)	PUNCT
admet-1335	232	9	1463	1463	NUM
admet-1335	232	10	-	-	SYM
admet-1335	232	11	1470	1470	NUM
admet-1335	232	12	.	.	PUNCT
admet-1335	233	1	https://dx.doi.org/10.13005/bpj/2018	https://dx.doi.org/10.13005/bpj/2018	NOUN
admet-1335	233	2	.	.	PUNCT
admet-1335	234	1	[	[	X
admet-1335	234	2	16	16	NUM
admet-1335	234	3	]	]	X
admet-1335	234	4	i.	i.	NOUN
admet-1335	234	5	dimitrov	dimitrov	PROPN
admet-1335	234	6	,	,	PUNCT
admet-1335	234	7	m.	m.	NOUN
admet-1335	234	8	atanasova	atanasova	PROPN
admet-1335	234	9	.	.	PUNCT
admet-1335	235	1	allerscreener	allerscreener	PROPN
admet-1335	235	2	–	–	PUNCT
admet-1335	235	3	a	a	DET
admet-1335	235	4	server	server	NOUN
admet-1335	235	5	for	for	ADP
admet-1335	235	6	allergenicity	allergenicity	NOUN
admet-1335	235	7	and	and	CCONJ
admet-1335	235	8	cross	cross	ADJ
admet-1335	235	9	-	-	ADJ
admet-1335	235	10	reactivity	reactivity	ADJ
admet-1335	235	11	prediction	prediction	NOUN
admet-1335	235	12	.	.	PUNCT
admet-1335	236	1	cybernetics	cybernetic	NOUN
admet-1335	236	2	and	and	CCONJ
admet-1335	236	3	information	information	NOUN
admet-1335	236	4	technologies	technology	NOUN
admet-1335	236	5	20	20	NUM
admet-1335	236	6	(	(	PUNCT
admet-1335	236	7	2020	2020	NUM
admet-1335	236	8	)	)	PUNCT
admet-1335	236	9	175184	175184	NUM
admet-1335	236	10	.	.	PUNCT
admet-1335	237	1	https://doi.org/10.2478/cait-2020-0071	https://doi.org/10.2478/cait-2020-0071	NOUN
admet-1335	237	2	.	.	PUNCT
admet-1335	238	1	[	[	X
admet-1335	238	2	17	17	NUM
admet-1335	238	3	]	]	X
admet-1335	238	4	n.	n.	PROPN
admet-1335	238	5	sharma	sharma	PROPN
admet-1335	238	6	,	,	PUNCT
admet-1335	238	7	s.	s.	PROPN
admet-1335	238	8	patiyal	patiyal	PROPN
admet-1335	238	9	,	,	PUNCT
admet-1335	238	10	a.	a.	NOUN
admet-1335	238	11	dhall	dhall	NOUN
admet-1335	238	12	,	,	PUNCT
admet-1335	238	13	a.	a.	NOUN
admet-1335	238	14	pande	pande	NOUN
admet-1335	238	15	,	,	PUNCT
admet-1335	238	16	c.	c.	PROPN
admet-1335	238	17	arora	arora	PROPN
admet-1335	238	18	,	,	PUNCT
admet-1335	238	19	g.p.s	g.p.s	PROPN
admet-1335	238	20	raghava	raghava	PROPN
admet-1335	238	21	.	.	PROPN
admet-1335	238	22	algpred	algpre	VERB
admet-1335	238	23	2.0	2.0	NUM
admet-1335	238	24	:	:	PUNCT
admet-1335	238	25	an	an	DET
admet-1335	238	26	improved	improved	ADJ
admet-1335	238	27	method	method	NOUN
admet-1335	238	28	for	for	ADP
admet-1335	238	29	predicting	predict	VERB
admet-1335	238	30	allergenic	allergenic	ADJ
admet-1335	238	31	proteins	protein	NOUN
admet-1335	238	32	and	and	CCONJ
admet-1335	238	33	mapping	mapping	NOUN
admet-1335	238	34	of	of	ADP
admet-1335	238	35	ige	ige	PROPN
admet-1335	238	36	epitopes	epitope	NOUN
admet-1335	238	37	.	.	PUNCT
admet-1335	239	1	briefings	briefing	NOUN
admet-1335	239	2	in	in	ADP
admet-1335	239	3	bioinformatics	bioinformatics	NOUN
admet-1335	239	4	22	22	NUM
admet-1335	239	5	(	(	PUNCT
admet-1335	239	6	2021	2021	NUM
admet-1335	239	7	)	)	PUNCT
admet-1335	239	8	bbaa294	bbaa294	PROPN
admet-1335	239	9	.	.	PUNCT
admet-1335	240	1	https://doi.org/10.1093/bib/bbaa294	https://doi.org/10.1093/bib/bbaa294	NOUN
admet-1335	240	2	.	.	PUNCT
admet-1335	241	1	https://doi.org/10.5599/admet.1335	https://doi.org/10.5599/admet.1335	NOUN
admet-1335	241	2	https://doi:10.1096	https://doi:10.1096	NOUN
admet-1335	241	3	/	/	SYM
admet-1335	241	4	fj.02	fj.02	PROPN
admet-1335	241	5	-	-	PUNCT
admet-1335	241	6	1052fje	1052fje	PROPN
admet-1335	241	7	https://doi.org/10.1093/jaoac/87.6.1391	https://doi.org/10.1093/jaoac/87.6.1391	PROPN
admet-1335	241	8	https://doi.org/10.1093/nar/gkl343	https://doi.org/10.1093/nar/gkl343	PROPN
admet-1335	241	9	https://doi.org/10.1371/journal.pone.0005861	https://doi.org/10.1371/journal.pone.0005861	PROPN
admet-1335	241	10	https://doi.org/10.2174/157340613804488341	https://doi.org/10.2174/157340613804488341	NOUN
admet-1335	241	11	https://doi.org/10.1109/bibm.2013.6732458	https://doi.org/10.1109/bibm.2013.6732458	PROPN
admet-1335	241	12	https://doi.org/10.1186/1471-2105-14-s6-s4	https://doi.org/10.1186/1471-2105-14-s6-s4	PROPN
admet-1335	241	13	https://doi.org/10.1093/bioinformatics/btt619	https://doi.org/10.1093/bioinformatics/btt619	NOUN
admet-1335	241	14	https://doi.org/10.1002/cem.2597	https://doi.org/10.1002/cem.2597	PROPN
admet-1335	241	15	https://doi.org/10.1007/s00894-014-2278-5	https://doi.org/10.1007/s00894-014-2278-5	NUM
admet-1335	241	16	https://doi.org/10.1093/bioinformatics/btu004	https://doi.org/10.1093/bioinformatics/btu004	NOUN
admet-1335	241	17	https://doi.org/10.1093/bioinformatics/btw767	https://doi.org/10.1093/bioinformatics/btw767	PROPN
admet-1335	241	18	https://doi.org/10.1080/1547691x.2018.1533904	https://doi.org/10.1080/1547691x.2018.1533904	VERB
admet-1335	241	19	https://doi.org/10.1093/bioinformatics/btz029	https://doi.org/10.1093/bioinformatics/btz029	NOUN
admet-1335	241	20	https://dx.doi.org/10.13005/bpj/2018	https://dx.doi.org/10.13005/bpj/2018	PROPN
admet-1335	241	21	https://doi.org/10.2478/cait-2020-0071	https://doi.org/10.2478/cait-2020-0071	PROPN
admet-1335	241	22	https://doi.org/10.1093/bib/bbaa294	https://doi.org/10.1093/bib/bbaa294	NOUN
admet-1335	241	23	pallavi	pallavi	VERB
admet-1335	241	24	and	and	CCONJ
admet-1335	241	25	rakshitha	rakshitha	PROPN
admet-1335	241	26	admet	admet	PROPN
admet-1335	241	27	&	&	CCONJ
admet-1335	241	28	dmpk	dmpk	PROPN
admet-1335	241	29	10(3	10(3	NUM
admet-1335	241	30	)	)	PUNCT
admet-1335	241	31	(	(	PUNCT
admet-1335	241	32	2022	2022	NUM
admet-1335	241	33	)	)	PUNCT
admet-1335	241	34	231	231	NUM
admet-1335	241	35	-	-	SYM
admet-1335	241	36	240	240	NUM
admet-1335	241	37	240	240	NUM
admet-1335	241	38	[	[	X
admet-1335	241	39	18	18	NUM
admet-1335	241	40	]	]	PUNCT
admet-1335	241	41	l.	l.	PROPN
admet-1335	241	42	wang	wang	PROPN
admet-1335	241	43	,	,	PUNCT
admet-1335	241	44	d.	d.	PROPN
admet-1335	241	45	niu	niu	PROPN
admet-1335	241	46	,	,	PUNCT
admet-1335	241	47	x.	x.	PROPN
admet-1335	241	48	zhao	zhao	PROPN
admet-1335	241	49	,	,	PUNCT
admet-1335	241	50	x.	x.	PROPN
admet-1335	241	51	wang	wang	PROPN
admet-1335	241	52	,	,	PUNCT
admet-1335	241	53	m.	m.	PROPN
admet-1335	241	54	hao	hao	PROPN
admet-1335	241	55	,	,	PUNCT
admet-1335	241	56	h.	h.	PROPN
admet-1335	241	57	che	che	PROPN
admet-1335	241	58	.	.	PUNCT
admet-1335	242	1	a	a	DET
admet-1335	242	2	comparative	comparative	ADJ
admet-1335	242	3	analysis	analysis	NOUN
admet-1335	242	4	of	of	ADP
admet-1335	242	5	novel	novel	ADJ
admet-1335	242	6	deep	deep	ADJ
admet-1335	242	7	learning	learning	NOUN
admet-1335	242	8	and	and	CCONJ
admet-1335	242	9	ensemble	ensemble	ADJ
admet-1335	242	10	learning	learning	NOUN
admet-1335	242	11	models	model	NOUN
admet-1335	242	12	to	to	PART
admet-1335	242	13	predict	predict	VERB
admet-1335	242	14	the	the	DET
admet-1335	242	15	allergenicity	allergenicity	NOUN
admet-1335	242	16	of	of	ADP
admet-1335	242	17	food	food	NOUN
admet-1335	242	18	proteins	protein	NOUN
admet-1335	242	19	.	.	PUNCT
admet-1335	243	1	foods	food	NOUN
admet-1335	243	2	10	10	NUM
admet-1335	243	3	(	(	PUNCT
admet-1335	243	4	2021	2021	NUM
admet-1335	243	5	)	)	PUNCT
admet-1335	243	6	809	809	NUM
admet-1335	243	7	.	.	PUNCT
admet-1335	244	1	https://doi.org/10.3390/foods10040809	https://doi.org/10.3390/foods10040809	PROPN
admet-1335	244	2	.	.	PUNCT
admet-1335	245	1	[	[	X
admet-1335	245	2	19	19	NUM
admet-1335	245	3	]	]	X
admet-1335	245	4	m.s	m.s	PROPN
admet-1335	245	5	.	.	PROPN
admet-1335	245	6	venkatarajan	venkatarajan	PROPN
admet-1335	245	7	,	,	PUNCT
admet-1335	245	8	w.	w.	NOUN
admet-1335	245	9	braun	braun	PROPN
admet-1335	245	10	.	.	PUNCT
admet-1335	246	1	new	new	ADJ
admet-1335	246	2	quantitative	quantitative	ADJ
admet-1335	246	3	descriptors	descriptor	NOUN
admet-1335	246	4	of	of	ADP
admet-1335	246	5	amino	amino	ADJ
admet-1335	246	6	acids	acid	NOUN
admet-1335	246	7	based	base	VERB
admet-1335	246	8	on	on	ADP
admet-1335	246	9	multidimensional	multidimensional	ADJ
admet-1335	246	10	scaling	scaling	NOUN
admet-1335	246	11	of	of	ADP
admet-1335	246	12	a	a	DET
admet-1335	246	13	large	large	ADJ
admet-1335	246	14	number	number	NOUN
admet-1335	246	15	of	of	ADP
admet-1335	246	16	physical	physical	ADJ
admet-1335	246	17	–	–	PUNCT
admet-1335	246	18	chemical	chemical	NOUN
admet-1335	246	19	properties	property	NOUN
admet-1335	246	20	.	.	PUNCT
admet-1335	247	1	molecular	molecular	ADJ
admet-1335	247	2	modeling	modeling	NOUN
admet-1335	247	3	annual	annual	ADJ
admet-1335	247	4	7	7	NUM
admet-1335	247	5	(	(	PUNCT
admet-1335	247	6	2001	2001	NUM
admet-1335	247	7	)	)	PUNCT
admet-1335	247	8	445453	445453	NUM
admet-1335	247	9	.	.	PUNCT
admet-1335	248	1	https://doi.org/10.1007/s00894-001-0058-5	https://doi.org/10.1007/s00894-001-0058-5	PROPN
admet-1335	248	2	.	.	PUNCT
admet-1335	249	1	[	[	X
admet-1335	249	2	20	20	NUM
admet-1335	249	3	]	]	SYM
admet-1335	249	4	i.a	i.a	PROPN
admet-1335	249	5	.	.	PROPN
admet-1335	249	6	doytchinova	doytchinova	PROPN
admet-1335	249	7	,	,	PUNCT
admet-1335	249	8	d.r	d.r	PROPN
admet-1335	249	9	.	.	PROPN
admet-1335	249	10	flower	flower	PROPN
admet-1335	249	11	.	.	PUNCT
admet-1335	250	1	vaxijen	vaxijen	NOUN
admet-1335	250	2	:	:	PUNCT
admet-1335	250	3	a	a	DET
admet-1335	250	4	server	server	NOUN
admet-1335	250	5	for	for	ADP
admet-1335	250	6	prediction	prediction	NOUN
admet-1335	250	7	of	of	ADP
admet-1335	250	8	protective	protective	ADJ
admet-1335	250	9	antigens	antigen	NOUN
admet-1335	250	10	,	,	PUNCT
admet-1335	250	11	tumour	tumour	NOUN
admet-1335	250	12	antigens	antigen	NOUN
admet-1335	250	13	and	and	CCONJ
admet-1335	250	14	subunit	subunit	NOUN
admet-1335	250	15	vaccines	vaccine	NOUN
admet-1335	250	16	.	.	PUNCT
admet-1335	251	1	bmc	bmc	ADJ
admet-1335	251	2	bioinformatics	bioinformatics	NOUN
admet-1335	251	3	8	8	NUM
admet-1335	251	4	(	(	PUNCT
admet-1335	251	5	2007	2007	NUM
admet-1335	251	6	)	)	PUNCT
admet-1335	251	7	1	1	NUM
admet-1335	251	8	-	-	SYM
admet-1335	251	9	7	7	NUM
admet-1335	251	10	.	.	PUNCT
admet-1335	252	1	https://dx.doi.org/10.1186%2f1471-2105-8-4	https://dx.doi.org/10.1186%2f1471-2105-8-4	PROPN
admet-1335	252	2	.	.	PUNCT
admet-1335	253	1	©	©	NOUN
admet-1335	253	2	2022	2022	NUM
admet-1335	253	3	by	by	ADP
admet-1335	253	4	the	the	DET
admet-1335	253	5	authors	author	NOUN
admet-1335	253	6	;	;	PUNCT
admet-1335	253	7	licensee	licensee	PROPN
admet-1335	253	8	iapc	iapc	PROPN
admet-1335	253	9	,	,	PUNCT
admet-1335	253	10	zagreb	zagreb	PROPN
admet-1335	253	11	,	,	PUNCT
admet-1335	253	12	croatia	croatia	PROPN
admet-1335	253	13	.	.	PUNCT
admet-1335	254	1	this	this	DET
admet-1335	254	2	article	article	NOUN
admet-1335	254	3	is	be	AUX
admet-1335	254	4	an	an	DET
admet-1335	254	5	open	open	ADJ
admet-1335	254	6	-	-	PUNCT
admet-1335	254	7	access	access	NOUN
admet-1335	254	8	article	article	NOUN
admet-1335	254	9	distributed	distribute	VERB
admet-1335	254	10	under	under	ADP
admet-1335	254	11	the	the	DET
admet-1335	254	12	terms	term	NOUN
admet-1335	254	13	and	and	CCONJ
admet-1335	254	14	conditions	condition	NOUN
admet-1335	254	15	of	of	ADP
admet-1335	254	16	the	the	DET
admet-1335	254	17	creative	creative	ADJ
admet-1335	254	18	commons	common	NOUN
admet-1335	254	19	attribution	attribution	NOUN
admet-1335	254	20	license	license	NOUN
admet-1335	254	21	(	(	PUNCT
admet-1335	254	22	http://creativecommons.org/licenses/by/3.0/	http://creativecommons.org/licenses/by/3.0/	PROPN
admet-1335	254	23	)	)	PUNCT
admet-1335	254	24	https://doi.org/10.3390/foods10040809	https://doi.org/10.3390/foods10040809	PROPN
admet-1335	254	25	https://doi.org/10.1007/s00894-001-0058-5	https://doi.org/10.1007/s00894-001-0058-5	NUM
admet-1335	255	1	https://dx.doi.org/10.1186%2f1471-2105-8-4	https://dx.doi.org/10.1186%2f1471-2105-8-4	PROPN
admet-1335	255	2	http://creativecommons.org/licenses/by/3.0/	http://creativecommons.org/licenses/by/3.0/	PROPN