{"id":"https://openalex.org/W4206322192","doi":"https://doi.org/10.1109/bibm52615.2021.9669359","title":"Representation Learning for Multi-omics Data with Heterogeneous Gene Regulatory Network","display_name":"Representation Learning for Multi-omics Data with Heterogeneous Gene Regulatory Network","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4206322192","doi":"https://doi.org/10.1109/bibm52615.2021.9669359"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669359","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5101416654","display_name":"Xiaoshuang Liu","orcid":"https://orcid.org/0000-0002-8829-7245"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoshuang Liu","raw_affiliation_strings":["PingAn Health Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PingAn Health Technology","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054517375","display_name":"Xian Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xian Xu","raw_affiliation_strings":["PingAn Health Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PingAn Health Technology","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100927768","display_name":"Xiao Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao Xu","raw_affiliation_strings":["PingAn Health Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PingAn Health Technology","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631401","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0003-0569-2176"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["PingAn Health Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PingAn Health Technology","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023775139","display_name":"Guotong Xie","orcid":"https://orcid.org/0000-0002-2772-8961"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guotong Xie","raw_affiliation_strings":["PingAn Health Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PingAn Health Technology","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5203,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57914339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"702","last_page":"705"},"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":0.9969000220298767,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9930999875068665,"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":0.7239297032356262},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5822769403457642},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5615778565406799},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5603764653205872},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49131789803504944},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4911174476146698},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.45711493492126465},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.444887638092041},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.44082701206207275},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4363096058368683},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.358015239238739},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21095308661460876},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.1132049560546875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239297032356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5822769403457642},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5615778565406799},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5603764653205872},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49131789803504944},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4911174476146698},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.45711493492126465},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.444887638092041},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.44082701206207275},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4363096058368683},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.358015239238739},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21095308661460876},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.1132049560546875},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669359","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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":21,"referenced_works":["https://openalex.org/W1544691147","https://openalex.org/W2053835153","https://openalex.org/W2110503722","https://openalex.org/W2161770119","https://openalex.org/W2171322586","https://openalex.org/W2782454362","https://openalex.org/W2889646458","https://openalex.org/W2899510892","https://openalex.org/W2900569176","https://openalex.org/W2921485464","https://openalex.org/W2964236544","https://openalex.org/W2967844557","https://openalex.org/W2990427224","https://openalex.org/W3005552578","https://openalex.org/W3017317719","https://openalex.org/W3034288498","https://openalex.org/W3038260279","https://openalex.org/W3100495486","https://openalex.org/W3165439041","https://openalex.org/W6772452955","https://openalex.org/W6780729216"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W3037187668","https://openalex.org/W2611989081","https://openalex.org/W4234772502","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W2380685755","https://openalex.org/W3048601286","https://openalex.org/W2965925734","https://openalex.org/W4285218279"],"abstract_inverted_index":{"To":[0],"derive":[1,130],"expressive":[2,131],"representations":[3,132],"from":[4],"high-dimensional":[5],"and":[6,103,121,149],"sparse":[7],"multi-omics":[8,74,172],"samples,":[9],"there":[10],"has":[11,160],"been":[12],"existing":[13],"research":[14],"attempting":[15],"to":[16,26,85,110,153,163],"incorporate":[17],"Gene":[18],"Regulatory":[19],"Network":[20],"(GRN)":[21],"as":[22],"a":[23,44,58,94,104,125,154],"prior":[24],"knowledge":[25,66],"enhance":[27],"deep":[28],"learning":[29,72,96,106],"models.":[30],"However,":[31],"these":[32],"methods":[33],"generally":[34],"just":[35,43],"considered":[36],"homogeneous":[37],"GRNs":[38],"with":[39,114],"simple":[40],"structures":[41],"containing":[42],"single":[45,49],"gene/interaction":[46],"type":[47],"for":[48,70,133],"omics":[50],"data":[51,117],"analysis.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56,128],"propose":[57],"new":[59,144],"framework":[60,145],"MoHeG":[61,77,159],"that":[62],"infuses":[63],"the":[64,87,112,140,143,161],"abundant":[65],"in":[67,118,168],"heterogeneous":[68,91],"GRN":[69],"representation":[71],"of":[73,90,142,156,171],"data.":[75,173],"Particularly,":[76],"first":[78],"adopts":[79],"an":[80,100,165],"interaction-specific":[81],"graph":[82,88],"attention":[83],"network":[84,113],"represent":[86],"structure":[89],"GRN.":[92],"Then,":[93],"self-supervised":[95],"strategy,":[97],"which":[98],"combines":[99],"auto-encoder":[101],"task":[102],"contrastive":[105],"task,":[107],"is":[108],"utilized":[109],"pre-train":[111],"unlabeled":[115],"gene":[116],"both":[119,147],"detail":[120],"distinctiveness":[122],"level.":[123],"Through":[124],"fine-tuning":[126],"approach,":[127],"can":[129],"various":[134],"downstream":[135],"tasks.":[136],"Our":[137],"experiments":[138],"demonstrate":[139],"effectiveness":[141],"on":[146],"sufficient":[148],"insufficient":[150],"datasets,":[151],"compared":[152],"series":[155],"state-of-the-art":[157],"baselines.":[158],"potential":[162],"become":[164],"advanced":[166],"encoder":[167],"analysis":[169],"pipeline":[170]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}