{"id":"https://openalex.org/W4306317360","doi":"https://doi.org/10.1145/3511808.3557346","title":"Heterogeneous Graph Attention Network for Drug-Target Interaction Prediction","display_name":"Heterogeneous Graph Attention Network for Drug-Target Interaction Prediction","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317360","doi":"https://doi.org/10.1145/3511808.3557346"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557346","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557346","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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/A5100331933","display_name":"Mei Li","orcid":"https://orcid.org/0000-0003-2313-7969"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mei Li","raw_affiliation_strings":["Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057847421","display_name":"Xiangrui Cai","orcid":"https://orcid.org/0000-0001-5039-0922"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrui Cai","raw_affiliation_strings":["Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101937754","display_name":"Linyu Li","orcid":"https://orcid.org/0009-0005-8626-0608"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linyu Li","raw_affiliation_strings":["Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077412882","display_name":"Sihan Xu","orcid":"https://orcid.org/0000-0002-6887-6231"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihan Xu","raw_affiliation_strings":["Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059824709","display_name":"Hua Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Ji","raw_affiliation_strings":["Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1166","last_page":"1176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"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":1.0,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9943000078201294,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8018845319747925},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.618000864982605},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.5970050692558289},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.5682309865951538},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.44564521312713623},{"id":"https://openalex.org/keywords/biological-network","display_name":"Biological network","score":0.4237854480743408},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.41747209429740906},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36127740144729614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35441190004348755},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.17254868149757385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8018845319747925},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.618000864982605},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.5970050692558289},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.5682309865951538},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.44564521312713623},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.4237854480743408},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41747209429740906},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36127740144729614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35441190004348755},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.17254868149757385},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557346","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557346","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4817874346","display_name":null,"funder_award_id":"62002178","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2122863289","https://openalex.org/W2124001239","https://openalex.org/W2137052779","https://openalex.org/W2142572836","https://openalex.org/W2145578524","https://openalex.org/W2152864198","https://openalex.org/W2153838454","https://openalex.org/W2259538443","https://openalex.org/W2294516783","https://openalex.org/W2743104969","https://openalex.org/W2753953057","https://openalex.org/W2767891136","https://openalex.org/W2807792492","https://openalex.org/W2889321024","https://openalex.org/W2924557457","https://openalex.org/W2945027804","https://openalex.org/W2951512731","https://openalex.org/W2952522777","https://openalex.org/W2964321699","https://openalex.org/W2998496395","https://openalex.org/W3033050543","https://openalex.org/W3093194543","https://openalex.org/W3096561213","https://openalex.org/W3096999989","https://openalex.org/W3097145107","https://openalex.org/W3107527779","https://openalex.org/W3113831423","https://openalex.org/W3126516421","https://openalex.org/W3130727496","https://openalex.org/W3136918052","https://openalex.org/W3165913101","https://openalex.org/W3167367835","https://openalex.org/W3167575787","https://openalex.org/W3167993868","https://openalex.org/W3175599101","https://openalex.org/W3176294187","https://openalex.org/W3188463051","https://openalex.org/W3192421672","https://openalex.org/W3217681006","https://openalex.org/W4206369686","https://openalex.org/W4206777097","https://openalex.org/W4224309748","https://openalex.org/W6720006811"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W4376641153","https://openalex.org/W2070875936","https://openalex.org/W4250391473","https://openalex.org/W3045075405","https://openalex.org/W4302292679","https://openalex.org/W4241625287","https://openalex.org/W2050788868","https://openalex.org/W4295885776","https://openalex.org/W2027634686"],"abstract_inverted_index":{"Identification":[0],"of":[1,38,153],"drug-target":[2],"interactions":[3],"(DTIs)":[4],"is":[5,170,191],"crucial":[6],"for":[7,71,181],"drug":[8,11],"discovery":[9],"and":[10,35,63,85,155],"repositioning.":[12],"Existing":[13],"graph":[14,54,70,77,94],"neural":[15],"network":[16,56],"(GNN)":[17],"based":[18],"methods":[19,139],"only":[20],"aggregate":[21],"information":[22,113],"from":[23,80,115,131,164,175],"directly":[24,110],"connected":[25],"nodes":[26,117],"restricted":[27],"in":[28,42,66,151],"a":[29,32],"drug-related":[30],"or":[31],"target-related":[33],"network,":[34],"are":[36],"incapable":[37],"capturing":[39],"long-range":[40],"dependencies":[41],"the":[43,52,60,67,82,86,128,132,146,165,176],"biological":[44,68,143],"heterogeneous":[45,53,69,76,142],"graph.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50,90,125],"propose":[51],"attention":[55,95],"(HGAN)":[57],"to":[58,149,183],"capture":[59],"complex":[61],"structures":[62],"rich":[64],"semantics":[65],"DTI":[72,186],"prediction.":[73],"HGAN":[74,135,182],"enhances":[75],"structure":[78],"learning":[79],"both":[81],"intra-layer":[83,177],"perspective":[84,167,178],"inter-layer":[87,133,166],"perspective.":[88,134],"Concretely,":[89],"develop":[91],"an":[92],"enhanced":[93],"diffusion":[96],"layer":[97],"(EGADL),":[98],"which":[99],"efficiently":[100],"builds":[101],"connections":[102],"between":[103],"node":[104],"pairs":[105],"that":[106,160,174],"may":[107],"not":[108],"be":[109],"connected,":[111],"enabling":[112],"passing":[114],"important":[116],"multiple":[118,123],"hops":[119],"away.":[120],"By":[121],"stacking":[122],"EGADLs,":[124],"further":[126],"enlarge":[127],"receptive":[129,162],"field":[130],"advances":[136],"15":[137],"state-of-the-art":[138],"on":[140],"two":[141],"datasets,":[144],"achieving":[145],"results":[147],"near":[148],"1":[150],"terms":[152],"AUC":[154],"AUPR.":[156],"We":[157],"also":[158],"find":[159],"enlarging":[161],"fields":[163],"(stacking":[168],"layers)":[169],"more":[171],"effective":[172],"than":[173],"(attention":[179],"diffusion)":[180],"achieve":[184],"promising":[185],"prediction":[187],"performances.":[188],"The":[189],"code":[190],"available":[192],"at":[193],"https://github.com/Zora-LM/HGAN-DTI.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}