{"id":"https://openalex.org/W3115409560","doi":"https://doi.org/10.1093/bioinformatics/btaa796","title":"Adversarial deconfounding autoencoder for learning robust gene expression embeddings","display_name":"Adversarial deconfounding autoencoder for learning robust gene expression embeddings","publication_year":2020,"publication_date":"2020-09-11","ids":{"openalex":"https://openalex.org/W3115409560","doi":"https://doi.org/10.1093/bioinformatics/btaa796","mag":"3115409560","pmid":"https://pubmed.ncbi.nlm.nih.gov/33381842"},"language":"en","primary_location":{"id":"doi:10.1093/bioinformatics/btaa796","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btaa796","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/36/Supplement_2/i573/35337257/btaa796.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"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":"Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://academic.oup.com/bioinformatics/article-pdf/36/Supplement_2/i573/35337257/btaa796.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072198355","display_name":"Ayse B. Dincer","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayse B Dincer","raw_affiliation_strings":["Paul G. Allen School of Computer Science & Engineering, University of Washington , Seattle, WA 98195, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Paul G. Allen School of Computer Science & Engineering, University of Washington , Seattle, WA 98195, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006900734","display_name":"Joseph D. Janizek","orcid":"https://orcid.org/0000-0003-1804-7133"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph D Janizek","raw_affiliation_strings":["Medical Scientist Training Program, University of Washington , Seattle, WA 98195, USA","Paul G. Allen School of Computer Science & Engineering, University of Washington , Seattle, WA 98195, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical Scientist Training Program, University of Washington , Seattle, WA 98195, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"Paul G. Allen School of Computer Science & Engineering, University of Washington , Seattle, WA 98195, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028723221","display_name":"Su\u2010In Lee","orcid":"https://orcid.org/0000-0001-5833-5215"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Su-In Lee","raw_affiliation_strings":["Paul G. Allen School of Computer Science & Engineering, University of Washington , Seattle, WA 98195, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Paul G. Allen School of Computer Science & Engineering, University of Washington , Seattle, WA 98195, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028723221"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":{"value":3618,"currency":"USD","value_usd":3618},"apc_paid":null,"fwci":2.7518,"has_fulltext":false,"cited_by_count":87,"citation_normalized_percentile":{"value":0.91492907,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"36","issue":"Supplement_2","first_page":"i573","last_page":"i582"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.24789999425411224,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.24789999425411224,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.23100000619888306,"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":0.1160999983549118,"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/autoencoder","display_name":"Autoencoder","score":0.9017866849899292},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6852951645851135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6518393754959106},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.651597797870636},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.6051714420318604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5927338004112244},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47866448760032654},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.47381746768951416},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4561937749385834},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.44411975145339966},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42939502000808716},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38835272192955017},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.2657429575920105},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.23590457439422607},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1946403682231903},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18242239952087402},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.11453649401664734}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9017866849899292},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6852951645851135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6518393754959106},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.651597797870636},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.6051714420318604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5927338004112244},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47866448760032654},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.47381746768951416},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4561937749385834},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.44411975145339966},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42939502000808716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38835272192955017},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.2657429575920105},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.23590457439422607},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1946403682231903},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18242239952087402},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.11453649401664734},{"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/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D015870","descriptor_name":"Gene Expression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015870","descriptor_name":"Gene Expression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015870","descriptor_name":"Gene Expression","qualifier_ui":null,"qualifier_name":null,"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/bioinformatics/btaa796","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btaa796","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/36/Supplement_2/i573/35337257/btaa796.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"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":"Bioinformatics","raw_type":"journal-article"},{"id":"pmid:33381842","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33381842","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":"Bioinformatics (Oxford, England)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:7773484","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7773484","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1093/bioinformatics/btaa796","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btaa796","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/36/Supplement_2/i573/35337257/btaa796.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"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":"Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1284677684","display_name":null,"funder_award_id":"R01 AG061132","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G1415851307","display_name":null,"funder_award_id":"R01 NIA AG 061132","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3403114034","display_name":null,"funder_award_id":"R35 GM 128638","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7207891620","display_name":null,"funder_award_id":"R35 GM128638","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W1812256879","https://openalex.org/W2011474181","https://openalex.org/W2018663224","https://openalex.org/W2020541351","https://openalex.org/W2025183726","https://openalex.org/W2038437697","https://openalex.org/W2049446938","https://openalex.org/W2085934079","https://openalex.org/W2089468765","https://openalex.org/W2100495367","https://openalex.org/W2104877015","https://openalex.org/W2104979975","https://openalex.org/W2107665951","https://openalex.org/W2109363337","https://openalex.org/W2109816625","https://openalex.org/W2113253187","https://openalex.org/W2128920415","https://openalex.org/W2130598050","https://openalex.org/W2132165198","https://openalex.org/W2137499573","https://openalex.org/W2139345901","https://openalex.org/W2147013674","https://openalex.org/W2150542002","https://openalex.org/W2161922342","https://openalex.org/W2164943005","https://openalex.org/W2211868589","https://openalex.org/W2259632819","https://openalex.org/W2313339984","https://openalex.org/W2546563948","https://openalex.org/W2555502666","https://openalex.org/W2775061087","https://openalex.org/W2951209146","https://openalex.org/W2952631022","https://openalex.org/W2978541146","https://openalex.org/W3006064320","https://openalex.org/W3027038786","https://openalex.org/W6637618735","https://openalex.org/W6675853627","https://openalex.org/W6676167818","https://openalex.org/W6682535766"],"related_works":["https://openalex.org/W2372020181","https://openalex.org/W2156531654","https://openalex.org/W1581723585","https://openalex.org/W4378714697","https://openalex.org/W2294330161","https://openalex.org/W2940472653","https://openalex.org/W2253069048","https://openalex.org/W2804553224","https://openalex.org/W140709781","https://openalex.org/W3214340375"],"abstract_inverted_index":{"MOTIVATION:":[0],"Increasing":[1],"number":[2],"of":[3,11,59,63,133],"gene":[4,125,188],"expression":[5,29,126,189],"profiles":[6],"has":[7],"enabled":[8],"the":[9,56,117,156,164,208,213],"use":[10],"complex":[12],"models,":[13],"such":[14],"as":[15,172,175],"deep":[16],"unsupervised":[17],"neural":[18,135],"networks,":[19],"to":[20,55,71,73,91,100,106,123,140,154,166,185],"extract":[21],"a":[22,84],"latent":[23,127],"space":[24,215],"from":[25,80,103,158],"these":[26],"profiles.":[27],"However,":[28],"profiles,":[30],"especially":[31],"when":[32],"collected":[33],"in":[34,53,212],"large":[35],"numbers,":[36],"inherently":[37],"contain":[38],"variations":[39],"introduced":[40],"by":[41],"technical":[42],"artifacts":[43],"(e.g.":[44,51],"batch":[45],"effects)":[46],"and":[47,149,216,231,240],"uninteresting":[48],"biological":[49,209],"variables":[50],"age)":[52],"addition":[54],"true":[57,104],"signals":[58,105,210],"interest.":[60],"These":[61],"sources":[62],"variations,":[64],"called":[65],"confounders,":[66],"produce":[67],"embeddings":[68,168,199],"that":[69,144,159,169,193,200,226],"fail":[70],"transfer":[72],"different":[74,92,221],"domains,":[75],"i.e.":[76],"an":[77,138,142,151],"embedding":[78,143],"learned":[79],"one":[81],"dataset":[82],"with":[83],"specific":[85],"confounder":[86,157,204,222],"distribution":[87],"does":[88],"not":[89,202],"generalize":[90,218],"distributions.":[93],"To":[94],"remedy":[95],"this":[96,113],"problem,":[97],"we":[98,115,191],"attempt":[99],"disentangle":[101],"confounders":[102],"generate":[107,141,167,198],"biologically":[108],"informative":[109],"embeddings.":[110],"RESULTS:":[111],"In":[112],"article,":[114],"introduce":[116],"Adversarial":[118],"Deconfounding":[119],"AutoEncoder":[120],"(AD-AE)":[121],"approach":[122],"deconfounding":[124,233],"spaces.":[128],"The":[129],"AD-AE":[130,184,227],"model":[131,195],"consists":[132],"two":[134,186],"networks:":[136],"(i)":[137,197],"autoencoder":[139,230],"can":[145,170,196],"reconstruct":[146],"original":[147,214],"measurements,":[148],"(ii)":[150,206],"adversary":[152],"trained":[153],"predict":[155],"embedding.":[160],"We":[161,224],"jointly":[162],"train":[163],"networks":[165],"encode":[171,203],"much":[173],"information":[174],"possible":[176],"without":[177],"encoding":[178],"any":[179],"confounding":[180],"signal.":[181],"By":[182],"applying":[183],"distinct":[187],"datasets,":[190],"show":[192],"our":[194],"do":[201],"information,":[205],"conserve":[207],"present":[211],"(iii)":[217],"successfully":[219],"across":[220],"domains.":[223],"demonstrate":[225],"outperforms":[228],"standard":[229],"other":[232],"approaches.":[234],"AVAILABILITY":[235],"AND":[236],"IMPLEMENTATION:":[237],"Our":[238],"code":[239],"data":[241,249],"are":[242,250],"available":[243,251],"at":[244,252],"https://gitlab.cs.washington.edu/abdincer/ad-ae.":[245],"SUPPLEMENTARY":[246],"INFORMATION:":[247],"Supplementary":[248],"Bioinformatics":[253],"online.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":37},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":10}],"updated_date":"2026-06-24T13:16:06.693445","created_date":"2025-10-10T00:00:00"}