{"id":"https://openalex.org/W4406238014","doi":"https://doi.org/10.1109/bibm62325.2024.10822466","title":"Dual Interaction and Kernel-Diverse Network for Accurate Drug-Target Binding Affinity Prediction","display_name":"Dual Interaction and Kernel-Diverse Network for Accurate Drug-Target Binding Affinity Prediction","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406238014","doi":"https://doi.org/10.1109/bibm62325.2024.10822466"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822466","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/A5119013597","display_name":"Yulong Wu","orcid":"https://orcid.org/0009-0000-7832-7802"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulong Wu","raw_affiliation_strings":["Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100733501","display_name":"Jin Xie","orcid":"https://orcid.org/0000-0002-1268-1363"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Xie","raw_affiliation_strings":["Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100557889","display_name":"Jing Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Nie","raw_affiliation_strings":["Chongqing University,School of School of Microelectronics and Communication Engineering,Chongqing,China,400044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of School of Microelectronics and Communication Engineering,Chongqing,China,400044","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084681436","display_name":"Jian Hu","orcid":"https://orcid.org/0000-0003-3896-6938"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Hu","raw_affiliation_strings":["Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102001561","display_name":"Yuansong Zeng","orcid":"https://orcid.org/0009-0003-6470-0671"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuansong Zeng","raw_affiliation_strings":["Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Big Data and Software Engineering,Chongqing,China,400044","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"860","last_page":"863"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T11016","display_name":"Monoclonal and Polyclonal Antibodies Research","score":0.9205999970436096,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12867","display_name":"Advanced Biosensing Techniques and Applications","score":0.9126999974250793,"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/dual","display_name":"Dual (grammatical number)","score":0.6775287985801697},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.623066246509552},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6040531992912292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4583030045032501},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39600682258605957},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21784552931785583},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07993772625923157}],"concepts":[{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6775287985801697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.623066246509552},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6040531992912292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4583030045032501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39600682258605957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21784552931785583},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07993772625923157},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822466","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":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.46000000834465027}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2035585923","https://openalex.org/W2086286404","https://openalex.org/W2097117768","https://openalex.org/W2109991441","https://openalex.org/W2785947426","https://openalex.org/W2809216727","https://openalex.org/W3096561213","https://openalex.org/W3207312583","https://openalex.org/W4313452755","https://openalex.org/W4390659208","https://openalex.org/W4390992116","https://openalex.org/W4391011450"],"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-target":[0],"binding":[1,5,48,112,145],"affinities":[2],"measure":[3],"the":[4,13,56,74,105,129,136],"strength":[6],"between":[7,138],"drugs":[8,60,77,108,139],"and":[9,43,61,67,78,81,97,109,116,140,156],"targets,":[10,80],"serving":[11],"as":[12],"foundation":[14],"for":[15,46,120],"computer-aided":[16],"drug":[17,115],"design.":[18],"The":[19,111],"existing":[20,165],"methods":[21,166],"based":[22],"on":[23,144,151,167],"neural":[24],"network":[25,45],"rarely":[26],"incorporate":[27],"knowledge":[28],"from":[29,55,88],"biochemistry,":[30],"which":[31],"limits":[32],"their":[33,79,82],"performance.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38,90,127],"propose":[39,91],"a":[40,92,98],"dual":[41],"interaction":[42],"kernel-diverse":[44],"drug-target":[47],"affinity":[49,122],"prediction,":[50],"termed":[51],"DTANet,":[52],"drawing":[53],"inspiration":[54,87],"biochemical":[57],"properties":[58,75],"of":[59,76,107,114],"targets.":[62,110],"Specifically,":[63],"since":[64],"functional":[65],"groups":[66],"peptide":[68],"chains":[69],"are":[70,172],"pivotal":[71],"in":[72],"determining":[73],"lengths":[83],"vary":[84],"significantly.":[85],"Drawing":[86],"this,":[89,126],"Kernel-diverse":[93],"Two-stream":[94],"Network":[95],"(KTN)":[96],"Cross-Scale":[99],"Interaction":[100,131],"Module":[101,132],"(CSIM)":[102],"to":[103,134,142,164],"extract":[104],"features":[106],"site":[113],"target":[117],"is":[118],"crucial":[119],"precise":[121],"prediction.":[123],"Inspired":[124],"by":[125],"introduce":[128],"Drug-Target":[130],"(DTIM)":[133],"explore":[135],"relationships":[137],"targets":[141],"focus":[143],"sites.":[146],"Experiments":[147],"have":[148],"been":[149],"conducted":[150],"two":[152],"popular":[153],"benchmarks:":[154],"KIBA":[155],"Davis.":[157],"Our":[158],"DTANet":[159],"obtains":[160],"superior":[161],"performance":[162],"compared":[163],"both":[168],"datasets.":[169],"Source":[170],"codes":[171],"available":[173],"at":[174],"https://github.com/202324131016T/DTANet.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}