{"id":"https://openalex.org/W2963517668","doi":"https://doi.org/10.1109/bibm.2018.8621379","title":"Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis","display_name":"Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2963517668","doi":"https://doi.org/10.1109/bibm.2018.8621379","mag":"2963517668"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2018.8621379","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2018.8621379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5007885072","display_name":"Tianle Ma","orcid":"https://orcid.org/0000-0003-2309-1489"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianle Ma","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, New York"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, New York","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013588572","display_name":"Aidong Zhang","orcid":"https://orcid.org/0000-0001-9723-3246"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aidong Zhang","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, New York"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, New York","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007885072"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":1.7619,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.85648964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"702","last_page":"707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9986000061035156,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9986000061035156,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9984999895095825,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9564999938011169,"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/autoencoder","display_name":"Autoencoder","score":0.7221832871437073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470946669578552},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.46996423602104187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4165847897529602},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15159285068511963},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14413109421730042}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7221832871437073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470946669578552},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.46996423602104187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4165847897529602},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15159285068511963},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14413109421730042}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2018.8621379","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2018.8621379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1019830208","https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W1966331733","https://openalex.org/W1987219048","https://openalex.org/W1989277387","https://openalex.org/W2022401242","https://openalex.org/W2054141820","https://openalex.org/W2096173332","https://openalex.org/W2135253885","https://openalex.org/W2184188583","https://openalex.org/W2255847468","https://openalex.org/W2292492942","https://openalex.org/W2474421929","https://openalex.org/W2541638185","https://openalex.org/W2590019597","https://openalex.org/W2619383789","https://openalex.org/W2790179710","https://openalex.org/W2795686629","https://openalex.org/W2795867722","https://openalex.org/W2795989238","https://openalex.org/W2796033668","https://openalex.org/W2807733000","https://openalex.org/W2810565934","https://openalex.org/W2919115771","https://openalex.org/W2950035161","https://openalex.org/W2950757414","https://openalex.org/W2963144883","https://openalex.org/W2964121744","https://openalex.org/W4230962320","https://openalex.org/W4237335579","https://openalex.org/W4293568373","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6686207219","https://openalex.org/W6691697006","https://openalex.org/W6721136770","https://openalex.org/W6753195712","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4220775285"],"abstract_inverted_index":{"Multi-omic":[0],"data":[1,13,26,60,82],"provides":[2],"multiple":[3],"views":[4],"of":[5,11,21,36,43],"the":[6,18,28,41,58,117],"same":[7],"patients.":[8],"Integrative":[9],"analysis":[10],"multi-omic":[12,25,59,81],"is":[14,38,45,48,123],"crucial":[15],"to":[16,50,79,95,105,130],"elucidate":[17],"molecular":[19],"underpinning":[20],"disease":[22,140],"etiology.":[23],"However,":[24],"has":[27],"\u201cbig":[29],"p,":[30],"small":[31],"N\u201d":[32],"problem":[33],"(the":[34],"number":[35,42],"features":[37],"large,":[39],"but":[40],"samples":[44],"small),":[46],"it":[47,64],"challenging":[49],"train":[51],"a":[52,70],"complicated":[53],"machine":[54],"learning":[55,94],"model":[56],"from":[57],"alone":[61],"and":[62,99,110,134],"make":[63],"generalize":[65],"well.":[66],"Here":[67],"we":[68],"propose":[69],"framework":[71,90,122],"termed":[72],"Multi-view":[73],"Factorization":[74],"AutoEncoder":[75],"with":[76,83],"network":[77,109,114],"constraints":[78,115],"integrate":[80,106],"domain":[84],"knowledge":[85],"(biological":[86],"interaction":[87,108],"networks).":[88],"Our":[89],"employs":[91],"deep":[92],"representation":[93],"learn":[96],"feature":[97,107],"embeddings":[98,101],"patient":[100,111],"simultaneously,":[102],"enabling":[103],"us":[104],"view":[112],"similarity":[113],"into":[116],"training":[118],"objective.":[119],"The":[120],"whole":[121],"end-to-end":[124],"differentiable.":[125],"We":[126],"applied":[127],"our":[128],"approach":[129],"two":[131],"TCGA":[132],"datasets":[133],"achieved":[135],"satisfactory":[136],"results":[137],"on":[138],"predicting":[139],"Progression-Free":[141],"Interval":[142],"(PFI)":[143],"event.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
