{"id":"https://openalex.org/W4297253404","doi":"https://doi.org/10.1093/bib/bbac409","title":"BioGPT: generative pre-trained transformer for biomedical text generation and mining","display_name":"BioGPT: generative pre-trained transformer for biomedical text generation and mining","publication_year":2022,"publication_date":"2022-09-24","ids":{"openalex":"https://openalex.org/W4297253404","doi":"https://doi.org/10.1093/bib/bbac409","pmid":"https://pubmed.ncbi.nlm.nih.gov/36156661"},"language":"en","primary_location":{"id":"doi:10.1093/bib/bbac409","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac409","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":["arxiv","crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.10341","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030131487","display_name":"Renqian Luo","orcid":"https://orcid.org/0000-0002-9062-3484"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renqian Luo","raw_affiliation_strings":["Microsoft Research Asia , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia , Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038673755","display_name":"Liai Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liai Sun","raw_affiliation_strings":["Peking University , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University , Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021772140","display_name":"Yingce Xia","orcid":"https://orcid.org/0000-0001-9823-9033"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingce Xia","raw_affiliation_strings":["Microsoft Research Asia , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia , Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020025718","display_name":"Tao Qin","orcid":"https://orcid.org/0000-0002-9095-0776"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Qin","raw_affiliation_strings":["Microsoft Research Asia , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia , Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041857260","display_name":"Sheng Zhang","orcid":"https://orcid.org/0000-0003-3672-5436"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng Zhang","raw_affiliation_strings":["Microsoft Research , Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research , Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019494985","display_name":"Hoifung Poon","orcid":"https://orcid.org/0000-0002-9067-0918"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hoifung Poon","raw_affiliation_strings":["Microsoft Research , Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research , Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101884287","display_name":"Tie\u2010Yan Liu","orcid":"https://orcid.org/0000-0002-0476-8020"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tie-Yan Liu","raw_affiliation_strings":["Microsoft Research Asia , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia , Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5020025718","https://openalex.org/A5021772140"],"corresponding_institution_ids":["https://openalex.org/I4210113369"],"apc_list":{"value":4011,"currency":"USD","value_usd":4011},"apc_paid":null,"fwci":120.7209,"has_fulltext":false,"cited_by_count":961,"citation_normalized_percentile":{"value":0.99983143,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"23","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9977999925613403,"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/generative-grammar","display_name":"Generative grammar","score":0.749281644821167},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6855605840682983},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6161397099494934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4785062372684479},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40144556760787964},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1577337086200714},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07079517841339111}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.749281644821167},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6855605840682983},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6161397099494934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4785062372684479},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40144556760787964},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1577337086200714},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07079517841339111},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","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":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1093/bib/bbac409","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac409","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:36156661","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36156661","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":null},{"id":"pmh:oai:arXiv.org:2210.10341","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.10341","pdf_url":"https://arxiv.org/pdf/2210.10341","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.10341","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.10341","pdf_url":"https://arxiv.org/pdf/2210.10341","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1981208470","https://openalex.org/W2170189740","https://openalex.org/W2174775663","https://openalex.org/W2250521169","https://openalex.org/W2346452181","https://openalex.org/W2396881363","https://openalex.org/W2517194566","https://openalex.org/W2798734500","https://openalex.org/W2802226260","https://openalex.org/W2895715183","https://openalex.org/W2896457183","https://openalex.org/W2911489562","https://openalex.org/W2912512851","https://openalex.org/W2923014074","https://openalex.org/W2933138175","https://openalex.org/W2949212908","https://openalex.org/W2951231735","https://openalex.org/W2962784628","https://openalex.org/W2962808855","https://openalex.org/W2965373594","https://openalex.org/W2970482702","https://openalex.org/W2970771982","https://openalex.org/W2971258845","https://openalex.org/W2979826702","https://openalex.org/W3034617555","https://openalex.org/W3034902017","https://openalex.org/W3034999214","https://openalex.org/W3035219457","https://openalex.org/W3035324702","https://openalex.org/W3035763680","https://openalex.org/W3046375318","https://openalex.org/W3095696617","https://openalex.org/W3101327207","https://openalex.org/W3102021238","https://openalex.org/W3104415840","https://openalex.org/W3116427155","https://openalex.org/W3154872984","https://openalex.org/W3166508187","https://openalex.org/W3168090480","https://openalex.org/W3174770825","https://openalex.org/W3185341429","https://openalex.org/W3196690920","https://openalex.org/W3202242582","https://openalex.org/W3214342214","https://openalex.org/W4205185581","https://openalex.org/W4205807230","https://openalex.org/W4221153690","https://openalex.org/W4221165572","https://openalex.org/W4223491992","https://openalex.org/W4238846128","https://openalex.org/W4239019441","https://openalex.org/W4241901867","https://openalex.org/W4250526791","https://openalex.org/W4281644150","https://openalex.org/W4286985375","https://openalex.org/W4287817164","https://openalex.org/W4287824654","https://openalex.org/W4292779060","https://openalex.org/W4295253143","https://openalex.org/W4297068981","https://openalex.org/W4297801719","https://openalex.org/W4303105513","https://openalex.org/W4385245566","https://openalex.org/W4385573954","https://openalex.org/W6704842505","https://openalex.org/W6739901393","https://openalex.org/W6750384732","https://openalex.org/W6751097180","https://openalex.org/W6766673545","https://openalex.org/W6776814788","https://openalex.org/W6778883912","https://openalex.org/W6794495662","https://openalex.org/W6796537594","https://openalex.org/W6798057236","https://openalex.org/W6800996715","https://openalex.org/W6801409643"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2380075625","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Pre-trained":[0],"language":[1,20,29,34,95,109],"models":[2,30,119],"have":[3,64],"attracted":[4],"increasing":[5],"attention":[6],"in":[7,16,31,53],"the":[8,17,23,32,46,54,76,159],"biomedical":[9,55,74,100,107,164,171],"domain,":[10,35,56],"inspired":[11],"by":[12],"their":[13,82],"great":[14,66],"success":[15,67],"general":[18,33],"natural":[19,108],"domain.":[21],"Among":[22],"two":[24],"main":[25],"branches":[26],"of":[27,71,78,161],"pre-trained":[28,97],"i.e.":[36],"BERT":[37],"(and":[38,43],"its":[39,44],"variants)":[40],"and":[41,60,112,128,135,142],"GPT":[42],"variants),":[45],"first":[47],"one":[48],"has":[49],"been":[50],"extensively":[51],"studied":[52],"such":[57],"as":[58],"BioBERT":[59],"PubMedBERT.":[61],"While":[62],"they":[63],"achieved":[65],"on":[68,98,105,120,132,145,154,163],"a":[69,91,148],"variety":[70],"discriminative":[72],"downstream":[73],"tasks,":[75,140],"lack":[77],"generation":[79,156],"ability":[80],"constrains":[81],"application":[83],"scope.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88,124],"propose":[89],"BioGPT,":[90],"domain-specific":[92],"generative":[93],"Transformer":[94],"model":[96,116],"large-scale":[99],"literature.":[101],"We":[102],"evaluate":[103],"BioGPT":[104,162],"six":[106],"processing":[110],"tasks":[111],"demonstrate":[113],"that":[114],"our":[115],"outperforms":[117],"previous":[118],"most":[121],"tasks.":[122],"Especially,":[123],"get":[125],"44.98%,":[126],"38.42%":[127],"40.76%":[129],"F1":[130],"score":[131],"BC5CDR,":[133],"KD-DTI":[134],"DDI":[136],"end-to-end":[137],"relation":[138],"extraction":[139],"respectively,":[141],"78.2%":[143],"accuracy":[144],"PubMedQA,":[146],"creating":[147],"new":[149],"record.":[150],"Our":[151],"case":[152],"study":[153],"text":[155],"further":[157],"demonstrates":[158],"advantage":[160],"literature":[165],"to":[166],"generate":[167],"fluent":[168],"descriptions":[169],"for":[170],"terms.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":94},{"year":2025,"cited_by_count":374},{"year":2024,"cited_by_count":306},{"year":2023,"cited_by_count":185},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}