{"id":"https://openalex.org/W4414110730","doi":"https://doi.org/10.1109/jbhi.2025.3607904","title":"Enhancing Protein Structure Learning Using a Size-Guided Conditional Mixture-of-Experts","display_name":"Enhancing Protein Structure Learning Using a Size-Guided Conditional Mixture-of-Experts","publication_year":2025,"publication_date":"2025-09-10","ids":{"openalex":"https://openalex.org/W4414110730","doi":"https://doi.org/10.1109/jbhi.2025.3607904","pmid":"https://pubmed.ncbi.nlm.nih.gov/40928909"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2025.3607904","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2025.3607904","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011879942","display_name":"Mingzhi Yuan","orcid":"https://orcid.org/0000-0003-1322-7530"},"institutions":[{"id":"https://openalex.org/I133868755","display_name":"Shanghai Medical College of Fudan University","ror":"https://ror.org/01zntxs11","country_code":"CN","type":"education","lineage":["https://openalex.org/I133868755","https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingzhi Yuan","raw_affiliation_strings":["Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1322-7530","affiliations":[{"raw_affiliation_string":"Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I133868755"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ao Shen","orcid":"https://orcid.org/0009-0001-1937-6855"},"institutions":[{"id":"https://openalex.org/I133868755","display_name":"Shanghai Medical College of Fudan University","ror":"https://ror.org/01zntxs11","country_code":"CN","type":"education","lineage":["https://openalex.org/I133868755","https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Shen","raw_affiliation_strings":["Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-1937-6855","affiliations":[{"raw_affiliation_string":"Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I133868755"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Siqi Yin","orcid":"https://orcid.org/0000-0003-4719-8897"},"institutions":[{"id":"https://openalex.org/I133868755","display_name":"Shanghai Medical College of Fudan University","ror":"https://ror.org/01zntxs11","country_code":"CN","type":"education","lineage":["https://openalex.org/I133868755","https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Yin","raw_affiliation_strings":["Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4719-8897","affiliations":[{"raw_affiliation_string":"Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I133868755"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103062942","display_name":"Yingfan Ma","orcid":"https://orcid.org/0009-0004-7335-785X"},"institutions":[{"id":"https://openalex.org/I133868755","display_name":"Shanghai Medical College of Fudan University","ror":"https://ror.org/01zntxs11","country_code":"CN","type":"education","lineage":["https://openalex.org/I133868755","https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfan Ma","raw_affiliation_strings":["Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-7335-785X","affiliations":[{"raw_affiliation_string":"Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I133868755"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qiao Huang","orcid":"https://orcid.org/0009-0004-6221-1687"},"institutions":[{"id":"https://openalex.org/I133868755","display_name":"Shanghai Medical College of Fudan University","ror":"https://ror.org/01zntxs11","country_code":"CN","type":"education","lineage":["https://openalex.org/I133868755","https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Huang","raw_affiliation_strings":["Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-6221-1687","affiliations":[{"raw_affiliation_string":"Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I133868755"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039752906","display_name":"Manning Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I133868755","display_name":"Shanghai Medical College of Fudan University","ror":"https://ror.org/01zntxs11","country_code":"CN","type":"education","lineage":["https://openalex.org/I133868755","https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Manning Wang","raw_affiliation_strings":["Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9255-3897","affiliations":[{"raw_affiliation_string":"Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I133868755"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5011879942"],"corresponding_institution_ids":["https://openalex.org/I133868755"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12050325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":"4","first_page":"3173","last_page":"3183"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9541000127792358,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.939300000667572,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6700000166893005},{"id":"https://openalex.org/keywords/protein-structure-prediction","display_name":"Protein structure prediction","score":0.5573999881744385},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5299000144004822},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49380001425743103},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4823000133037567},{"id":"https://openalex.org/keywords/protein-function-prediction","display_name":"Protein function prediction","score":0.3986000120639801},{"id":"https://openalex.org/keywords/protein-structure","display_name":"Protein structure","score":0.3871999979019165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7497000098228455},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6700000166893005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.633400022983551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6279000043869019},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.5573999881744385},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5299000144004822},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49380001425743103},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4823000133037567},{"id":"https://openalex.org/C207060522","wikidata":"https://www.wikidata.org/wiki/Q7251473","display_name":"Protein function prediction","level":4,"score":0.3986000120639801},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.38440001010894775},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C2988224531","wikidata":"https://www.wikidata.org/wiki/Q20830730","display_name":"Network structure","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28679999709129333},{"id":"https://openalex.org/C11804247","wikidata":"https://www.wikidata.org/wiki/Q896177","display_name":"Protein\u2013protein interaction","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C147816474","wikidata":"https://www.wikidata.org/wiki/Q169525","display_name":"Protein engineering","level":3,"score":0.25440001487731934}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011487","descriptor_name":"Protein Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011487","descriptor_name":"Protein Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D030562","descriptor_name":"Databases, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030562","descriptor_name":"Databases, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2025.3607904","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2025.3607904","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:40928909","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40928909","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":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7754111381","display_name":null,"funder_award_id":"23S41900400","funder_id":"https://openalex.org/F4320336652","funder_display_name":"Science and Technology Innovation Plan Of Shanghai Science and Technology Commission"}],"funders":[{"id":"https://openalex.org/F4320336652","display_name":"Science and Technology Innovation Plan Of Shanghai Science and Technology Commission","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3,71,202],"learning":[4,72,203],"on":[5,73,129,142,204],"protein":[6,21,40,65,74,86,101,108,136,193,205],"structures":[7,13],"has":[8],"attracted":[9],"widespread":[10],"attention,":[11],"as":[12,196],"determine":[14],"proteins'":[15],"function.":[16],"A":[17],"series":[18],"of":[19,38,85,94,107,149,158],"structure-based":[20],"property":[22,137],"prediction":[23,138],"methods":[24,33],"have":[25],"been":[26],"proposed,":[27],"achieving":[28],"remarkable":[29],"performance.":[30,57,127],"However,":[31],"these":[32],"often":[34,191],"neglect":[35],"the":[36,39,80,83,104,112],"importance":[37],"size":[41,109,194],"and":[42,54,88,119,139,151,174],"fail":[43],"to":[44,49,114],"fully":[45],"leverage":[46],"it,":[47,130],"leading":[48],"biases":[50,98],"toward":[51,99],"certain":[52,100],"sizes":[53,87],"suboptimal":[55],"overall":[56],"To":[58],"address":[59],"this":[60],"issue,":[61],"we":[62,131],"propose":[63,132],"a":[64,133,156],"size-guided":[66],"conditional":[67],"mixture-of-experts":[68],"for":[69,135],"improving":[70],"structures.":[75,206],"It":[76],"can":[77,166],"adaptively":[78],"activate":[79],"sub-networks":[81,95],"with":[82,145],"guidance":[84,110],"network":[89,113],"features.":[90],"Its":[91],"flexible":[92],"combinations":[93],"help":[96],"mitigate":[97],"sizes,":[102],"while":[103],"deliberate":[105],"incorporation":[106],"enables":[111],"effectively":[115],"capture":[116],"both":[117],"universal":[118],"size-specific":[120],"characteristics,":[121],"resulting":[122],"in":[123,201],"more":[124],"accurate":[125],"predictive":[126],"Based":[128],"framework":[134],"benchmark":[140],"it":[141],"eight":[143],"tasks":[144,179],"two":[146],"representation":[147],"forms":[148],"proteins":[150],"three":[152],"different":[153],"dataset":[154],"splits,":[155],"total":[157],"forty-eight":[159],"tests.":[160],"Experiments":[161],"show":[162],"that":[163,189],"our":[164,186],"method":[165],"be":[167],"seamlessly":[168],"integrated":[169],"into":[170],"numerous":[171],"existing":[172],"models":[173],"achieve":[175],"performance":[176],"improvement":[177],"across":[178],"under":[180],"almost":[181],"all":[182],"settings.":[183],"More":[184],"importantly,":[185],"experiments":[187],"reveal":[188],"although":[190],"overlooked,":[192],"serves":[195],"an":[197],"important":[198],"prior":[199],"knowledge":[200]},"counts_by_year":[],"updated_date":"2026-04-07T06:01:17.266235","created_date":"2025-10-10T00:00:00"}