{"id":"https://openalex.org/W4403210547","doi":"https://doi.org/10.1109/cibcb58642.2024.10702130","title":"Predicting Cancer Driver Genes: Leveraging Graph Convolutional Networks and Ensemble Learning","display_name":"Predicting Cancer Driver Genes: Leveraging Graph Convolutional Networks and Ensemble Learning","publication_year":2024,"publication_date":"2024-08-27","ids":{"openalex":"https://openalex.org/W4403210547","doi":"https://doi.org/10.1109/cibcb58642.2024.10702130"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb58642.2024.10702130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb58642.2024.10702130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5018320026","display_name":"Renan Soares de Andrades","orcid":"https://orcid.org/0000-0003-1102-7359"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Renan Soares de Andrades","raw_affiliation_strings":["UFRGS Bioinformatics Core, HCPA,Institute of Informatics,Porto Alegre,RS,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UFRGS Bioinformatics Core, HCPA,Institute of Informatics,Porto Alegre,RS,Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039060913","display_name":"Mariana Recamonde\u2010Mendoza","orcid":"https://orcid.org/0000-0003-2800-1032"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Mariana Recamonde-Mendoza","raw_affiliation_strings":["UFRGS Bioinformatics Core, HCPA,Institute of Informatics,Porto Alegre,RS,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UFRGS Bioinformatics Core, HCPA,Institute of Informatics,Porto Alegre,RS,Brazil","institution_ids":["https://openalex.org/I130442723"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130442723"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20123162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9911999702453613,"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":0.9911999702453613,"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/T13937","display_name":"Genetics, Bioinformatics, and Biomedical Research","score":0.9794999957084656,"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":0.9785000085830688,"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":0.7722426056861877},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5772242546081543},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5583032369613647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4473504424095154},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4112168550491333},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24909600615501404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7722426056861877},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5772242546081543},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5583032369613647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4473504424095154},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4112168550491333},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24909600615501404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb58642.2024.10702130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb58642.2024.10702130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320322502","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado do Rio Grande do Sul","ror":"https://ror.org/05k49za97"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1994127362","https://openalex.org/W2009720434","https://openalex.org/W2017138237","https://openalex.org/W2101234009","https://openalex.org/W2557187647","https://openalex.org/W2614443510","https://openalex.org/W2889646458","https://openalex.org/W2898789672","https://openalex.org/W2949066452","https://openalex.org/W2963351448","https://openalex.org/W2972935357","https://openalex.org/W3006029259","https://openalex.org/W3043738080","https://openalex.org/W3047825284","https://openalex.org/W3121356850","https://openalex.org/W3156270925","https://openalex.org/W3203161883","https://openalex.org/W4210917993","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Cancer":[0],"driver":[1],"genes":[2,64,109],"(CDGs)":[3],"are":[4,10],"crucial":[5],"in":[6,104,122],"cancer":[7,123,148],"development":[8],"and":[9,40,76,135,142,151],"key":[11],"targets":[12],"for":[13,132,146],"treatment.":[14],"This":[15,125],"study":[16,126],"proposes":[17],"a":[18],"novel":[19],"approach":[20,92],"utilizing":[21],"Graph":[22,27],"Neural":[23],"Networks":[24,29],"(GNNs),":[25],"particularly":[26],"Convolutional":[28],"(GCNs),":[30],"to":[31,79],"predict":[32],"CDGs":[33,103,114],"by":[34],"integrating":[35,139],"protein-protein":[36],"interaction":[37],"(PPI)":[38],"networks":[39,51,145],"multi-omics":[41,140],"data.":[42],"We":[43,69],"optimized":[44],"GCN":[45],"hyperparameters":[46],"across":[47,66,115],"six":[48],"different":[49],"PPI":[50,144],"from":[52],"literature,":[53],"which":[54],"improved":[55],"predictive":[56],"accuracy.":[57],"A":[58],"consensus":[59],"model":[60],"was":[61],"created":[62],"using":[63],"identified":[65,93],"all":[67,116],"networks.":[68],"used":[70],"ensemble-based":[71],"methods,":[72],"including":[73,97],"majority":[74],"voting":[75],"score":[77],"aggregation,":[78],"identify":[80],"high-probability":[81],"CDGs.":[82],"Comparisons":[83],"showed":[84],"that":[85],"ensemble":[86],"models":[87],"outperformed":[88],"individual":[89],"models.":[90],"Our":[91],"several":[94],"candidate":[95],"genes,":[96],"some":[98],"previously":[99],"unclassified,":[100],"as":[101,113],"potential":[102,120],"various":[105],"cancers.":[106],"Notably,":[107],"33":[108],"were":[110],"consistently":[111],"predicted":[112],"networks,":[117],"highlighting":[118],"their":[119],"importance":[121],"development.":[124,154],"highlights":[127],"the":[128,136],"effectiveness":[129],"of":[130,138],"GNNs":[131],"CDG":[133],"prediction":[134],"value":[137],"data":[141],"diverse":[143],"advancing":[147],"genomics":[149],"research":[150],"targeted":[152],"therapy":[153]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}