{"id":"https://openalex.org/W4406260133","doi":"https://doi.org/10.1109/bibm62325.2024.10822148","title":"HCCL: Hierarchical Channels and Contrastive Learning for Drug-Gene Multi-Relation Prediction","display_name":"HCCL: Hierarchical Channels and Contrastive Learning for Drug-Gene Multi-Relation Prediction","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406260133","doi":"https://doi.org/10.1109/bibm62325.2024.10822148"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5113285250","display_name":"Yizhe Shang","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhe Shang","raw_affiliation_strings":["Shaanxi Normal University,School of Computer Science,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaanxi Normal University,School of Computer Science,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047948362","display_name":"Jianrui Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianrui Chen","raw_affiliation_strings":["Shaanxi Normal University,School of Computer Science,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaanxi Normal University,School of Computer Science,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058768577","display_name":"Xiujuan Lei","orcid":"https://orcid.org/0000-0002-9901-1732"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiujuan Lei","raw_affiliation_strings":["Shaanxi Normal University,School of Computer Science,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaanxi Normal University,School of Computer Science,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091157395","display_name":"Fang\u2010Xiang Wu","orcid":"https://orcid.org/0000-0002-4593-9332"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fang-Xiang Wu","raw_affiliation_strings":["University of Saskatchewan,Department of Mechanical Engineering, Division of Biomedical Engineering, and Department of Computer Science,Saskatoon,Canada,S7N 5A9"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Saskatchewan,Department of Mechanical Engineering, Division of Biomedical Engineering, and Department of Computer Science,Saskatoon,Canada,S7N 5A9","institution_ids":["https://openalex.org/I32625721"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3679","last_page":"3682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9850999712944031,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9767000079154968,"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/relation","display_name":"Relation (database)","score":0.723527193069458},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5521343350410461},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44677355885505676},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41313236951828003},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.323577344417572},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20261815190315247}],"concepts":[{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.723527193069458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5521343350410461},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44677355885505676},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41313236951828003},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.323577344417572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20261815190315247}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W1980129409","https://openalex.org/W2767891136","https://openalex.org/W2892880750","https://openalex.org/W2913067913","https://openalex.org/W3044145717","https://openalex.org/W3107626709","https://openalex.org/W4229033742","https://openalex.org/W4321254242","https://openalex.org/W4386980918","https://openalex.org/W4387840870","https://openalex.org/W4393158757","https://openalex.org/W4396954010","https://openalex.org/W6726873649","https://openalex.org/W6844194202"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Drug-gene":[0],"interaction":[1],"plays":[2],"a":[3,54],"crucial":[4],"role":[5],"in":[6,63],"drug":[7,65,72],"discovery":[8],"and":[9,25,38,58,76,86,118,132],"personalized":[10],"medicine.":[11],"Although":[12],"existing":[13],"methods":[14],"have":[15],"improved":[16],"the":[17,81,96,104,127,130,140],"accuracy":[18],"of":[19,71,84,129,143],"exploring":[20],"multiple":[21],"relationships":[22],"between":[23],"drugs":[24,85],"genes,":[26,87],"there":[27],"are":[28],"still":[29],"some":[30,43],"limitations,":[31],"such":[32],"as":[33],"susceptibility":[34],"to":[35,92,121],"data":[36],"sparsity":[37],"poor":[39],"generalization,":[40],"which":[41,64,125],"pose":[42],"challenges":[44],"for":[45,110],"practical":[46],"applications.":[47],"To":[48],"address":[49],"these":[50],"challenges,":[51],"we":[52,88,114],"propose":[53],"novel":[55],"Hierarchical":[56],"Channels":[57],"Contrastive":[59],"Learning":[60],"(HCCL)":[61],"framework":[62],"feature":[66,134],"extractor":[67],"captures":[68],"structural":[69],"information":[70,135],"molecules":[73],"from":[74],"atom":[75],"bond":[77],"channels.":[78],"After":[79],"obtaining":[80],"initial":[82],"features":[83],"employ":[89],"high-low-order":[90,123],"channels":[91],"update":[93],"them,":[94],"where":[95],"low-order":[97],"channel":[98,106],"adopts":[99],"graph":[100],"convolutional":[101],"networks":[102],"while":[103],"high-order":[105],"leverages":[107],"hypergraph":[108],"structures":[109],"message":[111],"propagation.":[112],"Finally,":[113],"adopt":[115],"contrastive":[116],"learning":[117],"inter-channel":[119],"attention":[120],"fuse":[122],"features,":[124],"improves":[126],"robustness":[128],"model":[131],"prevents":[133],"loss.":[136],"Experimental":[137],"results":[138],"demonstrate":[139],"superior":[141],"performance":[142],"HCCL.":[144]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
