{"id":"https://openalex.org/W4225891318","doi":"https://doi.org/10.1093/bib/bbac142","title":"An analysis of protein language model embeddings for fold prediction","display_name":"An analysis of protein language model embeddings for fold prediction","publication_year":2022,"publication_date":"2022-03-29","ids":{"openalex":"https://openalex.org/W4225891318","doi":"https://doi.org/10.1093/bib/bbac142","pmid":"https://pubmed.ncbi.nlm.nih.gov/35443054"},"language":"en","primary_location":{"id":"doi:10.1093/bib/bbac142","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac142","pdf_url":null,"source":{"id":"https://openalex.org/S91767247","display_name":"Briefings in Bioinformatics","issn_l":"1467-5463","issn":["1467-5463","1477-4054"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://digibug.ugr.es/bitstream/10481/80621/1/2022.02.07.479394v1.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039818706","display_name":"Amelia Villegas-Morcillo","orcid":"https://orcid.org/0000-0002-3286-049X"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Amelia Villegas-Morcillo","raw_affiliation_strings":["Department of Signal Theory, Telematics and Communications, University of Granada, Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory, Telematics and Communications, University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024291487","display_name":"\u00c1ngel M. G\u00f3mez","orcid":"https://orcid.org/0000-0002-9995-3068"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Angel M Gomez","raw_affiliation_strings":["Department of Signal Theory, Telematics and Communications, University of Granada, Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory, Telematics and Communications, University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028849516","display_name":"Victoria S\u00e1nchez","orcid":"https://orcid.org/0000-0003-1546-9728"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Victoria Sanchez","raw_affiliation_strings":["Department of Signal Theory, Telematics and Communications, University of Granada, Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory, Telematics and Communications, University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5039818706"],"corresponding_institution_ids":["https://openalex.org/I173304897"],"apc_list":{"value":4151,"currency":"USD","value_usd":4151},"apc_paid":null,"fwci":3.6338,"has_fulltext":true,"cited_by_count":50,"citation_normalized_percentile":{"value":0.94616689,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"23","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10521","display_name":"RNA and protein synthesis mechanisms","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.731897234916687},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6205064058303833},{"id":"https://openalex.org/keywords/fold","display_name":"Fold (higher-order function)","score":0.5878552794456482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5776345133781433},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.542704701423645},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49692538380622864},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4753955602645874},{"id":"https://openalex.org/keywords/protein-structure-prediction","display_name":"Protein structure prediction","score":0.47457006573677063},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.4535461664199829},{"id":"https://openalex.org/keywords/threading","display_name":"Threading (protein sequence)","score":0.4417327344417572},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4383033514022827},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41249340772628784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35447150468826294},{"id":"https://openalex.org/keywords/protein-structure","display_name":"Protein structure","score":0.34008997678756714},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12467673420906067}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.731897234916687},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6205064058303833},{"id":"https://openalex.org/C53942344","wikidata":"https://www.wikidata.org/wiki/Q951651","display_name":"Fold (higher-order function)","level":2,"score":0.5878552794456482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5776345133781433},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.542704701423645},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49692538380622864},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4753955602645874},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.47457006573677063},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.4535461664199829},{"id":"https://openalex.org/C200307862","wikidata":"https://www.wikidata.org/wiki/Q7797175","display_name":"Threading (protein sequence)","level":3,"score":0.4417327344417572},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4383033514022827},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41249340772628784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35447150468826294},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.34008997678756714},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12467673420906067},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1093/bib/bbac142","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac142","pdf_url":null,"source":{"id":"https://openalex.org/S91767247","display_name":"Briefings in Bioinformatics","issn_l":"1467-5463","issn":["1467-5463","1477-4054"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},{"id":"pmid:35443054","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35443054","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in bioinformatics","raw_type":"Journal Article"},{"id":"pmh:oai:digibug.ugr.es:10481/80621","is_oa":true,"landing_page_url":"https://hdl.handle.net/10481/80621","pdf_url":"https://digibug.ugr.es/bitstream/10481/80621/1/2022.02.07.479394v1.full.pdf","source":{"id":"https://openalex.org/S4306400567","display_name":"Institutional Repository of the University of Granada (University of Granada)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173304897","host_organization_name":"Universidad de Granada","host_organization_lineage":["https://openalex.org/I173304897"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:digibug.ugr.es:10481/80621","is_oa":true,"landing_page_url":"https://hdl.handle.net/10481/80621","pdf_url":"https://digibug.ugr.es/bitstream/10481/80621/1/2022.02.07.479394v1.full.pdf","source":{"id":"https://openalex.org/S4306400567","display_name":"Institutional Repository of the University of Granada (University of Granada)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173304897","host_organization_name":"Universidad de Granada","host_organization_lineage":["https://openalex.org/I173304897"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6899999976158142}],"awards":[{"id":"https://openalex.org/G1159817154","display_name":null,"funder_award_id":"BES-2017-079792","funder_id":"https://openalex.org/F4320314140","funder_display_name":"Family Process Institute"},{"id":"https://openalex.org/G300979063","display_name":null,"funder_award_id":"10.13039/501100011033","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G7399548993","display_name":null,"funder_award_id":"PID2019-104206GB-I00","funder_id":"https://openalex.org/F4320322930","funder_display_name":"Ministerio de Ciencia e Innovaci\u00f3n"}],"funders":[{"id":"https://openalex.org/F4320314140","display_name":"Family Process Institute","ror":"https://ror.org/03vd52t28"},{"id":"https://openalex.org/F4320322930","display_name":"Ministerio de Ciencia e Innovaci\u00f3n","ror":"https://ror.org/034900433"},{"id":"https://openalex.org/F4320335598","display_name":"Agencia Estatal de Investigaci\u00f3n","ror":"https://ror.org/003x0zc53"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4225891318.pdf","grobid_xml":"https://content.openalex.org/works/W4225891318.grobid-xml"},"referenced_works_count":106,"referenced_works":["https://openalex.org/W1501531009","https://openalex.org/W1522301498","https://openalex.org/W1924770834","https://openalex.org/W1936662467","https://openalex.org/W1996357466","https://openalex.org/W2033496784","https://openalex.org/W2064675550","https://openalex.org/W2085277871","https://openalex.org/W2095705004","https://openalex.org/W2098884353","https://openalex.org/W2102461176","https://openalex.org/W2105099387","https://openalex.org/W2108067237","https://openalex.org/W2109109045","https://openalex.org/W2119331235","https://openalex.org/W2130479394","https://openalex.org/W2131774270","https://openalex.org/W2136724628","https://openalex.org/W2139774535","https://openalex.org/W2145268834","https://openalex.org/W2146084306","https://openalex.org/W2147145103","https://openalex.org/W2148853951","https://openalex.org/W2151180344","https://openalex.org/W2160672912","https://openalex.org/W2163957306","https://openalex.org/W2165699943","https://openalex.org/W2168336675","https://openalex.org/W2191134648","https://openalex.org/W2243910093","https://openalex.org/W2514866683","https://openalex.org/W2550969987","https://openalex.org/W2557595285","https://openalex.org/W2562171514","https://openalex.org/W2566498094","https://openalex.org/W2604272474","https://openalex.org/W2605650084","https://openalex.org/W2612690371","https://openalex.org/W2747370968","https://openalex.org/W2783197164","https://openalex.org/W2805527642","https://openalex.org/W2810116194","https://openalex.org/W2889498145","https://openalex.org/W2896457183","https://openalex.org/W2914272550","https://openalex.org/W2940438782","https://openalex.org/W2949342052","https://openalex.org/W2953008890","https://openalex.org/W2962739339","https://openalex.org/W2964019776","https://openalex.org/W2964110616","https://openalex.org/W2972411752","https://openalex.org/W2980789587","https://openalex.org/W2980805969","https://openalex.org/W2982608875","https://openalex.org/W2989977616","https://openalex.org/W2994989159","https://openalex.org/W2995514860","https://openalex.org/W2998108143","https://openalex.org/W2999044305","https://openalex.org/W2999089077","https://openalex.org/W2999481648","https://openalex.org/W3021037500","https://openalex.org/W3044776631","https://openalex.org/W3046280678","https://openalex.org/W3049692992","https://openalex.org/W3083120907","https://openalex.org/W3084357007","https://openalex.org/W3092407503","https://openalex.org/W3093934303","https://openalex.org/W3095583226","https://openalex.org/W3099816816","https://openalex.org/W3104537585","https://openalex.org/W3106745904","https://openalex.org/W3112376646","https://openalex.org/W3118936575","https://openalex.org/W3126848411","https://openalex.org/W3144701084","https://openalex.org/W3146944767","https://openalex.org/W3177500196","https://openalex.org/W3177828909","https://openalex.org/W3181361429","https://openalex.org/W3186179742","https://openalex.org/W3205755169","https://openalex.org/W3211795435","https://openalex.org/W3215918380","https://openalex.org/W4206714742","https://openalex.org/W4206928576","https://openalex.org/W4212774754","https://openalex.org/W4225868104","https://openalex.org/W4242765109","https://openalex.org/W4246984456","https://openalex.org/W4288089799","https://openalex.org/W6631190155","https://openalex.org/W6640212811","https://openalex.org/W6674330103","https://openalex.org/W6684638663","https://openalex.org/W6726025202","https://openalex.org/W6727057065","https://openalex.org/W6755207826","https://openalex.org/W6756040250","https://openalex.org/W6768021236","https://openalex.org/W6769627184","https://openalex.org/W6770700894","https://openalex.org/W6772853553","https://openalex.org/W6785296276"],"related_works":["https://openalex.org/W2411998238","https://openalex.org/W2253761889","https://openalex.org/W2462594639","https://openalex.org/W2143233657","https://openalex.org/W3149404221","https://openalex.org/W2380350064","https://openalex.org/W2136856901","https://openalex.org/W2625160262","https://openalex.org/W2181585194","https://openalex.org/W2516036395"],"abstract_inverted_index":{"The":[0,159],"identification":[1],"of":[2,36,109,165],"the":[3,34,52,107,113,121,144,163,176,209],"protein":[4,26,46,61,81,220,231],"fold":[5,18,82,101,146,151],"class":[6],"is":[7,225],"a":[8,70,78,204,226],"challenging":[9],"problem":[10],"in":[11,33,69,185],"structural":[12],"biology.":[13],"Recent":[14],"computational":[15],"methods":[16],"for":[17,80,198],"prediction":[19,83,191],"leverage":[20],"deep":[21],"learning":[22],"techniques":[23],"to":[24,55,58,90,222,230],"extract":[25],"fold-representative":[27],"embeddings":[28,87,224],"mainly":[29],"using":[30,84],"evolutionary":[31],"information":[32,68],"form":[35],"multiple":[37],"sequence":[38],"alignment":[39],"(MSA)":[40],"as":[41,88,128,130],"input":[42,89],"source.":[43],"In":[44,73,103],"contrast,":[45],"language":[47],"models":[48,181],"(LM)":[49],"have":[50],"reshaped":[51],"field":[53],"thanks":[54],"their":[56],"ability":[57],"learn":[59],"efficient":[60],"representations":[62,221],"(protein-LM":[63],"embeddings)":[64],"from":[65,218],"purely":[66],"sequential":[67],"self-supervised":[71],"manner.":[72],"this":[74,214],"paper,":[75],"we":[76,105,193],"analyze":[77],"framework":[79],"pre-trained":[85],"protein-LM":[86,111,223],"several":[91,195],"fine-tuning":[92,180],"neural":[93,132],"network":[94],"models,":[95],"which":[96,202],"are":[97],"supervisedly":[98],"trained":[99],"with":[100,175],"labels.":[102],"particular,":[104],"compare":[106],"performance":[108,206],"six":[110],"embeddings:":[112],"long":[114],"short-term":[115],"memory-based":[116],"UniRep":[117],"and":[118,120,126,138,149,178,200],"SeqVec,":[119],"transformer-based":[122,166],"ESM-1b,":[123],"ESM-MSA,":[124],"ProtBERT":[125],"ProtT5;":[127],"well":[129,184],"three":[131],"networks:":[133],"Multi-Layer":[134],"Perceptron,":[135],"ResCNN-BGRU":[136],"(RBG)":[137],"Light-Attention":[139],"(LAT).":[140],"We":[141],"separately":[142],"evaluated":[143],"pairwise":[145],"recognition":[147],"(PFR)":[148],"direct":[150],"classification":[152],"(DFC)":[153],"tasks":[154],"on":[155],"well-known":[156],"benchmark":[157],"datasets.":[158],"results":[160],"indicate":[161],"that":[162,216],"combination":[164],"embeddings,":[167],"particularly":[168],"those":[169],"obtained":[170],"at":[171],"amino":[172],"acid":[173],"level,":[174],"RBG":[177],"LAT":[179],"performs":[182],"remarkably":[183],"both":[186],"tasks.":[187,233],"To":[188],"further":[189],"increase":[190],"accuracy,":[192],"propose":[194],"ensemble":[196],"strategies":[197],"PFR":[199],"DFC,":[201],"provide":[203],"significant":[205],"boost":[207],"over":[208],"current":[210],"state-of-the-art":[211],"results.":[212],"All":[213],"suggests":[215],"moving":[217],"traditional":[219],"very":[227],"promising":[228],"approach":[229],"fold-related":[232]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2025-10-10T00:00:00"}
