{"id":"https://openalex.org/W4220840971","doi":"https://doi.org/10.1186/s12859-022-04628-8","title":"A-Prot: protein structure modeling using MSA transformer","display_name":"A-Prot: protein structure modeling using MSA transformer","publication_year":2022,"publication_date":"2022-03-16","ids":{"openalex":"https://openalex.org/W4220840971","doi":"https://doi.org/10.1186/s12859-022-04628-8","pmid":"https://pubmed.ncbi.nlm.nih.gov/35296230"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-022-04628-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04628-8","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-022-04628-8","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-022-04628-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027399963","display_name":"Yiyu Hong","orcid":"https://orcid.org/0000-0001-6138-7083"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yiyu Hong","raw_affiliation_strings":["Arontier Co, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arontier Co, Seoul, Republic of Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066026979","display_name":"Juyong Lee","orcid":"https://orcid.org/0000-0003-1174-4358"},"institutions":[{"id":"https://openalex.org/I165507594","display_name":"Kangwon National University","ror":"https://ror.org/01mh5ph17","country_code":"KR","type":"education","lineage":["https://openalex.org/I165507594"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Juyong Lee","raw_affiliation_strings":["Arontier Co, Seoul, Republic of Korea. juyong.lee@kangwon.ac.kr","Department of Chemistry, Division of Chemistry and Biochemistry, Kangwon National University, Chuncheon, Republic of Korea. juyong.lee@kangwon.ac.kr","Arontier Co, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arontier Co, Seoul, Republic of Korea. juyong.lee@kangwon.ac.kr","institution_ids":[]},{"raw_affiliation_string":"Department of Chemistry, Division of Chemistry and Biochemistry, Kangwon National University, Chuncheon, Republic of Korea. juyong.lee@kangwon.ac.kr","institution_ids":["https://openalex.org/I165507594"]},{"raw_affiliation_string":"Arontier Co, Seoul, Republic of Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105988820","display_name":"Junsu Ko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junsu Ko","raw_affiliation_strings":["Arontier Co, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arontier Co, Seoul, Republic of Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027399963"],"corresponding_institution_ids":[],"apc_list":{"value":1690,"currency":"GBP","value_usd":2072},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2072},"fwci":1.5601,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.82513013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":"1","first_page":"93","last_page":"93"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.8458999991416931,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.8458999991416931,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.08269999921321869,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.006500000134110451,"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":0.7162339091300964},{"id":"https://openalex.org/keywords/protein-structure-prediction","display_name":"Protein structure prediction","score":0.6576919555664062},{"id":"https://openalex.org/keywords/casp","display_name":"CASP","score":0.5594888925552368},{"id":"https://openalex.org/keywords/dihedral-angle","display_name":"Dihedral angle","score":0.5339948534965515},{"id":"https://openalex.org/keywords/protein-structure","display_name":"Protein structure","score":0.4726352095603943},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41297537088394165},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4114657938480377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39537400007247925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3825054168701172},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.33927714824676514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3233131170272827},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.15071699023246765},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.0950116217136383},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08986112475395203}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7162339091300964},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.6576919555664062},{"id":"https://openalex.org/C66153294","wikidata":"https://www.wikidata.org/wiki/Q899291","display_name":"CASP","level":4,"score":0.5594888925552368},{"id":"https://openalex.org/C89025888","wikidata":"https://www.wikidata.org/wiki/Q911907","display_name":"Dihedral angle","level":4,"score":0.5339948534965515},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.4726352095603943},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41297537088394165},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4114657938480377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39537400007247925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3825054168701172},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.33927714824676514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3233131170272827},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.15071699023246765},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0950116217136383},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08986112475395203},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C112887158","wikidata":"https://www.wikidata.org/wiki/Q169324","display_name":"Hydrogen bond","level":3,"score":0.0},{"id":"https://openalex.org/C32909587","wikidata":"https://www.wikidata.org/wiki/Q11369","display_name":"Molecule","level":2,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011211","descriptor_name":"Electric Power Supplies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011211","descriptor_name":"Electric Power Supplies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011211","descriptor_name":"Electric Power Supplies","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":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12859-022-04628-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04628-8","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-022-04628-8","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:35296230","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35296230","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":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:doaj.org/article:2517f8bf0bef4da298141e1ed78a2b84","is_oa":true,"landing_page_url":"https://doaj.org/article/2517f8bf0bef4da298141e1ed78a2b84","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 23, Iss 1, Pp 1-11 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8925138","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8925138","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-022-04628-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04628-8","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-022-04628-8","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G6035103128","display_name":null,"funder_award_id":"2019M3E5D4066898","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G851535577","display_name":null,"funder_award_id":"2018R1C1B600543513","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220840971.pdf","grobid_xml":"https://content.openalex.org/works/W4220840971.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W136234207","https://openalex.org/W1979762151","https://openalex.org/W1982583124","https://openalex.org/W2065921821","https://openalex.org/W2107867854","https://openalex.org/W2114340287","https://openalex.org/W2120836664","https://openalex.org/W2132022258","https://openalex.org/W2136799255","https://openalex.org/W2138122982","https://openalex.org/W2302255633","https://openalex.org/W2557595285","https://openalex.org/W2949342052","https://openalex.org/W2950954328","https://openalex.org/W2957531855","https://openalex.org/W2967606876","https://openalex.org/W2971003495","https://openalex.org/W2972411752","https://openalex.org/W2983571096","https://openalex.org/W2987090428","https://openalex.org/W2997234557","https://openalex.org/W2999044305","https://openalex.org/W2999481648","https://openalex.org/W3010387158","https://openalex.org/W3037888463","https://openalex.org/W3111174583","https://openalex.org/W3124030253","https://openalex.org/W3133458480","https://openalex.org/W3146944767","https://openalex.org/W3166142427","https://openalex.org/W3175014854","https://openalex.org/W3177828909","https://openalex.org/W3178087467","https://openalex.org/W3183921815","https://openalex.org/W3185358186","https://openalex.org/W3186243460","https://openalex.org/W3193271391","https://openalex.org/W6691548924","https://openalex.org/W6767164110"],"related_works":["https://openalex.org/W2946599741","https://openalex.org/W2147472674","https://openalex.org/W2561391236","https://openalex.org/W1888349473","https://openalex.org/W2136856901","https://openalex.org/W3165545667","https://openalex.org/W4225106352","https://openalex.org/W47248631","https://openalex.org/W3171039768","https://openalex.org/W2058542300"],"abstract_inverted_index":{"BACKGROUND:":[0],"The":[1,43,174],"accuracy":[2],"of":[3,15,30,45,53,68,85,115,163,172,189,204,220],"protein":[4,105,118,222],"3D":[5,36,63,106,161],"structure":[6,107],"prediction":[7,72,92,224],"has":[8],"been":[9],"dramatically":[10],"improved":[11],"with":[12,206],"the":[13,21,49,66,71,116,154,160,164,178,199,218],"help":[14],"advances":[16],"in":[17],"deep":[18],"learning.":[19],"In":[20,98],"recent":[22],"CASP14,":[23],"Deepmind":[24],"demonstrated":[25,146],"that":[26,48,147,177,195],"their":[27],"new":[28,104],"version":[29],"AlphaFold":[31],"(AF)":[32],"produces":[33],"highly":[34],"accurate":[35,62,183],"models":[37,180],"almost":[38],"close":[39],"to":[40,61],"experimental":[41],"structures.":[42],"success":[44,67],"AF":[46],"shows":[47,176],"multiple":[50],"sequence":[51,55],"alignment":[52],"a":[54,78,82,90,103,142,215],"contains":[56],"rich":[57],"evolutionary":[58,200],"information,":[59],"leading":[60],"models.":[64,120],"Despite":[65],"AF,":[69],"only":[70],"code":[73],"is":[74,94],"open,":[75],"and":[76,125,131,137,167,201],"training":[77],"similar":[79],"model":[80,93],"requires":[81],"vast":[83],"amount":[84],"computational":[86,209],"resources.":[87],"Thus,":[88,211],"developing":[89],"lighter":[91],"still":[95],"necessary.":[96],"RESULTS:":[97],"this":[99],"study,":[100],"we":[101,158],"propose":[102],"modeling":[108,166,170],"method,":[109],"A-Prot,":[110],"using":[111],"MSA":[112,122],"Transformer,":[113],"one":[114],"state-of-the-art":[117],"language":[119],"An":[121],"feature":[123],"tensor":[124],"row":[126],"attention":[127],"maps":[128],"are":[129,181],"extracted":[130],"converted":[132],"into":[133],"2D":[134],"residue-residue":[135],"distance":[136],"dihedral":[138],"angle":[139],"predictions":[140],"for":[141,217],"given":[143],"MSA.":[144],"We":[145],"A-Prot":[148,179,196,212],"predicts":[149],"long-range":[150],"contacts":[151],"better":[152],"than":[153,184],"existing":[155],"methods.":[156,225],"Additionally,":[157],"modeled":[159],"structures":[162],"free":[165],"hard":[168],"template-based":[169],"targets":[171],"CASP14.":[173,190],"assessment":[175],"more":[182],"most":[185],"top":[186],"server":[187],"groups":[188],"CONCLUSION:":[191],"These":[192],"results":[193],"imply":[194],"accurately":[197],"captures":[198],"structural":[202],"information":[203],"proteins":[205],"relatively":[207],"low":[208],"cost.":[210],"can":[213],"provide":[214],"clue":[216],"development":[219],"other":[221],"property":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}