{"id":"https://openalex.org/W7117481492","doi":"https://doi.org/10.1109/tcbbio.2025.3648991","title":"Multimodal Hypergraph Representation Learning for Drug Synergy Prediction","display_name":"Multimodal Hypergraph Representation Learning for Drug Synergy Prediction","publication_year":2025,"publication_date":"2025-12-29","ids":{"openalex":"https://openalex.org/W7117481492","doi":"https://doi.org/10.1109/tcbbio.2025.3648991","pmid":"https://pubmed.ncbi.nlm.nih.gov/41460902"},"language":"en","primary_location":{"id":"doi:10.1109/tcbbio.2025.3648991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbbio.2025.3648991","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043","2998-4165"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5121518978","display_name":"Zheng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zhang","raw_affiliation_strings":["School of Biomedical Engineering, South-Central Minzu University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101814301","display_name":"Tong Luo","orcid":"https://orcid.org/0000-0002-2194-3011"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Luo","raw_affiliation_strings":["School of Biomedical Engineering, South-Central Minzu University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110367913","display_name":"Xian-Gan CHEN","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian-gan Chen","raw_affiliation_strings":["School of Biomedical Engineering, South-Central Minzu University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-6171-8564","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109700420","display_name":"Xiaofei Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Yang","raw_affiliation_strings":["School of Biomedical Engineering, South-Central Minzu University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114066469","display_name":"Jihong Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jihong Gong","raw_affiliation_strings":["School of Biomedical Engineering, South-Central Minzu University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64104105,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":"1","first_page":"518","last_page":"527"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.8432999849319458,"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":0.8432999849319458,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.08869999647140503,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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":0.020899999886751175,"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/hypergraph","display_name":"Hypergraph","score":0.8720999956130981},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5993000268936157},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5620999932289124},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5533000230789185},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.48100000619888306},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.47049999237060547},{"id":"https://openalex.org/keywords/drug-repositioning","display_name":"Drug repositioning","score":0.4122999906539917},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36649999022483826}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.8720999956130981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6338000297546387},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5993000268936157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5893999934196472},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5620999932289124},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5533000230789185},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5192000269889832},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.4122999906539917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3653999865055084},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34470000863075256},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27079999446868896}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004357","descriptor_name":"Drug Synergism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004357","descriptor_name":"Drug Synergism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004359","descriptor_name":"Drug Therapy, Combination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D004359","descriptor_name":"Drug Therapy, Combination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tcbbio.2025.3648991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbbio.2025.3648991","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043","2998-4165"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},{"id":"pmid:41460902","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41460902","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on computational biology and bioinformatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G872476790","display_name":null,"funder_award_id":"32170699","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":32,"referenced_works":["https://openalex.org/W2010427019","https://openalex.org/W2011810742","https://openalex.org/W2061061337","https://openalex.org/W2116341502","https://openalex.org/W2118151336","https://openalex.org/W2140822728","https://openalex.org/W2200017991","https://openalex.org/W2299417213","https://openalex.org/W2600452401","https://openalex.org/W2608863179","https://openalex.org/W2775061087","https://openalex.org/W2899070097","https://openalex.org/W3004500553","https://openalex.org/W3083074502","https://openalex.org/W3085990079","https://openalex.org/W3102269903","https://openalex.org/W3127930610","https://openalex.org/W3175806247","https://openalex.org/W3203908308","https://openalex.org/W3205950546","https://openalex.org/W3209882608","https://openalex.org/W4200519100","https://openalex.org/W4221065598","https://openalex.org/W4289315841","https://openalex.org/W4293214728","https://openalex.org/W4327676467","https://openalex.org/W4385751491","https://openalex.org/W4385799560","https://openalex.org/W4389317742","https://openalex.org/W4392393090","https://openalex.org/W4393093006","https://openalex.org/W4394812234"],"related_works":[],"abstract_inverted_index":{"Drug":[0],"combination":[1],"therapy":[2],"for":[3,196],"complex":[4],"diseases":[5],"is":[6,192],"currently":[7],"widely":[8],"utilized":[9],"in":[10,111],"clinical":[11],"treatment.":[12],"An":[13],"increasing":[14],"number":[15],"of":[16,81,95,108,127],"computational":[17],"methods":[18,30],"are":[19,104,121,151],"being":[20],"adopted":[21],"to":[22,114,123,143,153],"discover":[23],"new":[24],"drug":[25,42,63,96,102,109,183,199],"combinations.":[26,200],"However,":[27],"most":[28],"existing":[29],"mainly":[31],"focus":[32],"on":[33,166],"phenotypes,":[34],"while":[35],"ignoring":[36],"the":[37,67,75,112,138],"deep":[38],"level":[39],"interactions":[40],"between":[41],"pairs":[43,97,184],"and":[44,78,87,90,98,129,160,170,175],"cell":[45,88,99,130,186],"lines.":[46,100,187],"In":[47,157],"this":[48],"paper,":[49],"we":[50],"introduce":[51],"a":[52,71,145,193],"multimodal":[53],"hypergraph":[54,72,113],"representation":[55],"learning":[56],"approach":[57],"named":[58],"MHGSynergy,":[59],"aimed":[60],"at":[61],"predicting":[62],"synergies.":[64],"MHGSynergy":[65,163,176,191],"models":[66],"synergistic":[68,93,198],"relationship":[69],"as":[70,106],"by":[73],"considering":[74],"structure,":[76],"targets,":[77],"physicochemical":[79],"features":[80,103,126,136],"drugs.":[82],"The":[83],"nodes":[84,110],"represent":[85],"drugs":[86,128],"lines,":[89,131],"hyperedges":[91],"capture":[92],"triplets":[94],"Different":[101],"used":[105,152],"attributes":[107],"construct":[115],"three":[116],"hypergraphs.":[117],"Hypergraph":[118],"neural":[119],"networks":[120],"employed":[122],"update":[124],"embedding":[125,135],"then":[132],"input":[133],"these":[134,149],"into":[137],"channel":[139],"attention":[140],"fusion":[141],"module":[142],"obtain":[144],"comprehensive":[146],"representation.":[147],"Finally,":[148],"representations":[150],"build":[154],"predictive":[155],"models.":[156],"both":[158],"classification":[159],"regression":[161],"tasks,":[162],"performs":[164],"well":[165],"two":[167],"benchmark":[168],"datasets,":[169],"outperforming":[171],"those":[172],"baseline":[173],"methods,":[174],"has":[177],"unique":[178],"advantages":[179],"when":[180],"facing":[181],"unknown":[182],"or":[185],"We":[188],"believe":[189],"that":[190],"valuable":[194],"tool":[195],"discovering":[197]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-12-29T00:00:00"}
