{"id":"https://openalex.org/W4416251648","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227938","title":"Multi-Channel Learning Framework Based on Relation-Aware Transformer For Drug Synergy Prediction","display_name":"Multi-Channel Learning Framework Based on Relation-Aware Transformer For Drug Synergy Prediction","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251648","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227938"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5100649574","display_name":"Kaiyuan Zhang","orcid":"https://orcid.org/0000-0002-4983-9427"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiyuan Zhang","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642051","display_name":"Yifei Huang","orcid":"https://orcid.org/0000-0002-3077-0175"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yifei Huang","raw_affiliation_strings":["National University of Singapore,School of Computing,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore,School of Computing,Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100649067","display_name":"Runze Wang","orcid":"https://orcid.org/0009-0004-4767-6152"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runze Wang","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084159324","display_name":"Tianyi Zang","orcid":"https://orcid.org/0000-0003-0195-8731"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyi Zang","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112754141","display_name":"Yanli Zhao","orcid":"https://orcid.org/0000-0002-9231-8360"},"institutions":[{"id":"https://openalex.org/I116265982","display_name":"Qinghai University","ror":"https://ror.org/05h33bt13","country_code":"CN","type":"education","lineage":["https://openalex.org/I116265982"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanli Zhao","raw_affiliation_strings":["Qinghai University,Medical College,Xining,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qinghai University,Medical College,Xining,China","institution_ids":["https://openalex.org/I116265982"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.7649000287055969,"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":0.7649000287055969,"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":0.05869999900460243,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.03530000150203705,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.5631999969482422},{"id":"https://openalex.org/keywords/drug-repositioning","display_name":"Drug repositioning","score":0.4440999925136566},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41769999265670776},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.37549999356269836},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.351500004529953},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.35100001096725464},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.3353999853134155}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6535000205039978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6523000001907349},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.5631999969482422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506600022315979},{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.4440999925136566},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3813999891281128},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.37549999356269836},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.351500004529953},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3158000111579895},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.30660000443458557},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C535046627","wikidata":"https://www.wikidata.org/wiki/Q30612","display_name":"Clinical trial","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C114851261","wikidata":"https://www.wikidata.org/wiki/Q12147416","display_name":"Drug resistance","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326280","display_name":"Qinghai University","ror":"https://ror.org/05h33bt13"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1435191252","https://openalex.org/W1594591001","https://openalex.org/W1989086627","https://openalex.org/W1994663540","https://openalex.org/W1996486545","https://openalex.org/W2027155618","https://openalex.org/W2043398720","https://openalex.org/W2062533676","https://openalex.org/W2105253056","https://openalex.org/W2126726407","https://openalex.org/W2136549265","https://openalex.org/W2146980885","https://openalex.org/W2154747925","https://openalex.org/W2154851992","https://openalex.org/W2171676198","https://openalex.org/W2531057506","https://openalex.org/W2545245164","https://openalex.org/W2575228167","https://openalex.org/W2600452401","https://openalex.org/W2775061087","https://openalex.org/W2913560138","https://openalex.org/W2916879436","https://openalex.org/W2919115771","https://openalex.org/W2964434803","https://openalex.org/W2966787092","https://openalex.org/W3005970824","https://openalex.org/W3006386963","https://openalex.org/W3021393704","https://openalex.org/W3035011799","https://openalex.org/W3093030756","https://openalex.org/W3127930610","https://openalex.org/W3143789190","https://openalex.org/W3159120388","https://openalex.org/W3164087725","https://openalex.org/W3165146808","https://openalex.org/W3172530361","https://openalex.org/W3195831412","https://openalex.org/W3197302696","https://openalex.org/W3198409039","https://openalex.org/W3203908308","https://openalex.org/W4206405364","https://openalex.org/W4323031630","https://openalex.org/W4384818885","https://openalex.org/W4387440394"],"related_works":[],"abstract_inverted_index":{"Combined":[0],"therapeutic":[1],"strategies":[2],"have":[3,86,211],"demonstrated":[4],"their":[5],"importance":[6,54],"in":[7],"addressing":[8],"complex":[9,151],"diseases,":[10],"particularly":[11],"among":[12],"patient":[13],"populations":[14],"where":[15],"monotherapy":[16],"is":[17,74],"less":[18],"effective.":[19],"Compared":[20],"to":[21,96,98,135,149,182],"single":[22],"drug":[23,28,35,71,102,124,161,187],"treatments,":[24],"the":[25,32,39,156,176,184,195,213],"use":[26],"of":[27,34,41,67,179,186,198,215],"combinations":[29],"can":[30],"reduce":[31],"occurrence":[33],"resistance":[36],"and":[37,57,118,167,174,200],"enhance":[38,183],"efficacy":[40],"cancer":[42],"treatments.":[43],"Therefore,":[44],"developing":[45],"effective":[46],"combination":[47,72],"therapies":[48],"through":[49],"clinical":[50],"trials":[51],"holds":[52],"significant":[53],"for":[55,138],"researchers":[56,85],"society":[58],"as":[59],"a":[60,64,108,131,145],"whole.":[61],"However,":[62],"facing":[63],"vast":[65],"library":[66],"compounds,":[68],"conducting":[69],"high-throughput":[70],"screening":[73],"not":[75],"only":[76],"challenging":[77],"but":[78],"also":[79],"costly.":[80],"To":[81],"overcome":[82],"these":[83,180],"difficulties,":[84],"developed":[87,107],"various":[88],"computational":[89],"methods":[90],"that":[91],"utilize":[92,144],"biomedical":[93,168,202],"data":[94],"related":[95],"drugs":[97,199],"efficiently":[99],"identify":[100],"potential":[101],"combinations.":[103],"This":[104],"study":[105],"has":[106],"novel":[109],"multi-channel":[110,157],"representation":[111],"learning":[112,139],"framework":[113],"based":[114],"on":[115,207],"knowledge":[116,169],"graphs":[117,170],"Transformers":[119],"models,":[120],"aimed":[121],"at":[122],"predicting":[123],"synergy.":[125],"Unlike":[126],"full-graph":[127],"analysis,":[128],"we":[129,143,159],"employ":[130],"node-centric":[132],"sampling":[133],"strategy":[134],"extract":[136],"subgraphs":[137],"node":[140],"representations.":[141],"Furthermore,":[142],"relation-based":[146],"self-attention":[147],"mechanism":[148],"handle":[150],"relations":[152],"between":[153],"nodes.":[154],"Through":[155],"network,":[158],"input":[160],"molecular":[162],"structures,":[163],"cell":[164],"line":[165],"information,":[166],"into":[171],"different":[172],"channels,":[173],"fuse":[175],"feature":[177],"representations":[178],"channels":[181],"accuracy":[185],"synergy":[188],"prediction.":[189],"Our":[190],"model":[191],"benefits":[192],"from":[193],"both":[194],"structural":[196],"features":[197],"rich":[201],"background":[203],"information.":[204],"Extensive":[205],"experiments":[206],"two":[208],"representative":[209],"databases":[210],"validated":[212],"effectiveness":[214],"our":[216],"model.":[217]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}