{"id":"https://openalex.org/W7126024391","doi":"https://doi.org/10.1109/bibm66473.2025.11356349","title":"AFMCDR: An Adaptive Fusion Model to Predict Cancer Drug Responses Based on Hierarchical Feature Enhancement from Multi-Omics of Driver Mutations","display_name":"AFMCDR: An Adaptive Fusion Model to Predict Cancer Drug Responses Based on Hierarchical Feature Enhancement from Multi-Omics of Driver Mutations","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126024391","doi":"https://doi.org/10.1109/bibm66473.2025.11356349"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356349","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","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/A5124283851","display_name":"Weiliang Han","orcid":null},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiliang Han","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124284840","display_name":"Zhensong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhensong Wang","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041932219","display_name":"Jiajie Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajie Xing","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124150511","display_name":"Yuan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090902630","display_name":"Jianyuan Wang","orcid":"https://orcid.org/0000-0002-2109-358X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Wang","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China","Xiamen University,Department of Artificial Intelligence,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"Xiamen University,Department of Artificial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108047889","display_name":"Y\u00ec W\u00e1ng","orcid":"https://orcid.org/0000-0001-5697-0717"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Wang","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China","Xiamen University,Department of Artificial Intelligence,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"Xiamen University,Department of Artificial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5124283851"],"corresponding_institution_ids":["https://openalex.org/I2722730"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78221649,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"933","last_page":"940"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.4666999876499176,"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":0.4666999876499176,"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":0.2689000070095062,"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/T11287","display_name":"Cancer Genomics and Diagnostics","score":0.09319999814033508,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.5295000076293945},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5156999826431274},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.4562999904155731},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4108999967575073},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4099000096321106},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3961000144481659},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.39149999618530273},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.3880000114440918},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.3700000047683716},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3675999939441681}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6503999829292297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.616599977016449},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5295000076293945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5210000276565552},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5156999826431274},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.4562999904155731},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4099000096321106},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3961000144481659},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39149999618530273},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3880000114440918},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C3020340455","wikidata":"https://www.wikidata.org/wiki/Q974135","display_name":"Cancer drugs","level":3,"score":0.36070001125335693},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.3522999882698059},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3409999907016754},{"id":"https://openalex.org/C2994372470","wikidata":"https://www.wikidata.org/wiki/Q4118072","display_name":"Cancer cell lines","level":4,"score":0.33880001306533813},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C2994119904","wikidata":"https://www.wikidata.org/wiki/Q1251001","display_name":"Drug response","level":3,"score":0.33489999175071716},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C64903051","wikidata":"https://www.wikidata.org/wiki/Q2198549","display_name":"Drug development","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.29679998755455017},{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.2822999954223633},{"id":"https://openalex.org/C2777494893","wikidata":"https://www.wikidata.org/wiki/Q4781752","display_name":"Approved drug","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.2775000035762787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2533000111579895},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356349","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1604316295","https://openalex.org/W2016023958","https://openalex.org/W2042103473","https://openalex.org/W2043398720","https://openalex.org/W2057481835","https://openalex.org/W2094791588","https://openalex.org/W2103124714","https://openalex.org/W2108068107","https://openalex.org/W2136132422","https://openalex.org/W2955502047","https://openalex.org/W2974658886","https://openalex.org/W2992551937","https://openalex.org/W3008395627","https://openalex.org/W3087571032","https://openalex.org/W3116278528","https://openalex.org/W3117393006","https://openalex.org/W3130891725","https://openalex.org/W3148071990","https://openalex.org/W3154997013","https://openalex.org/W3164920770","https://openalex.org/W3176450501","https://openalex.org/W3183641295","https://openalex.org/W3192677404","https://openalex.org/W3209882608","https://openalex.org/W4252208101","https://openalex.org/W4297179162","https://openalex.org/W4312214400","https://openalex.org/W4366824201","https://openalex.org/W4385245566","https://openalex.org/W4387455607","https://openalex.org/W4387675955","https://openalex.org/W4389504970","https://openalex.org/W4389856652","https://openalex.org/W4390971075","https://openalex.org/W4392854166","https://openalex.org/W4397049553","https://openalex.org/W4398226202","https://openalex.org/W4401831408","https://openalex.org/W4404853127","https://openalex.org/W4408323900"],"related_works":[],"abstract_inverted_index":{"Prediction":[0],"of":[1,20,57,66,72,195,225,248],"cancer":[2,73,96,211,240],"drug":[3,67,97,112,123,176,212,226,241],"response":[4,124,227],"based":[5],"on":[6,23,104,199],"deep":[7,145],"learning":[8,172],"methods":[9,208],"has":[10,79],"become":[11],"the":[12,55,64,70,140,148,193,223],"basis":[13],"for":[14,32,42,190,238],"personalized":[15],"medicine.":[16],"A":[17],"large":[18],"amount":[19],"multi-omics":[21,38,102,196],"data":[22,39,103,121],"human":[24],"cell":[25,108],"lines":[26,109],"and":[27,62,110,144,152,246],"anti-cancer":[28],"drugs":[29,61],"are":[30,250],"available":[31,251],"this":[33,43],"task.":[34,44],"Feature":[35],"extraction":[36],"from":[37],"is":[40,234],"essential":[41],"Driver":[45],"mutations":[46,75,106],"affect":[47,63,122],"key":[48,92,127],"signaling":[49],"pathways,":[50],"which":[51],"can":[52],"significantly":[53,221],"alter":[54],"sensitivity":[56],"tumor":[58],"cells":[59],"to":[60,76,160],"prediction":[65],"response.":[68,98,242],"However,":[69],"contribution":[71],"driver":[74,105,218],"model":[77],"performance":[78,224],"not":[80],"been":[81],"fully":[82],"investigated.":[83],"We":[84],"propose":[85,131,154,183],"AFMCDR,":[86],"a":[87,115,126,132,155,170,184,235],"novel":[88],"approach":[89],"that":[90,137,174,204,217,232],"addresses":[91],"challenges":[93],"in":[94,107,117,209],"predicting":[95,210,239],"AFMCDR":[99,205,233,249],"innovatively":[100],"utilizes":[101],"multidimensional":[111],"data,":[113],"filling":[114],"gap":[116],"understanding":[118],"how":[119],"these":[120],"mechanisms,":[125],"research":[128],"area;":[129],"we":[130,153,168,182],"hierarchical":[133],"feature":[134,142],"enhancement":[135],"network":[136],"captures":[138],"both":[139],"histological":[141],"level":[143],"associations":[146,162],"at":[147,252],"biological":[149,185],"entity":[150],"level;":[151],"biomedical":[156,164,179],"crossnetwork":[157],"attention":[158],"mechanism":[159,189],"capture":[161],"between":[163],"entities.":[165],"In":[166],"addition,":[167],"design":[169],"representation":[171],"method":[173],"combines":[175],"responses":[177],"with":[178],"information.":[180],"Finally,":[181],"network-based":[186],"adaptive":[187],"fusion":[188,194],"dynamically":[191],"optimizing":[192],"features.":[197],"Experiments":[198],"two":[200],"benchmark":[201],"datasets":[202,247],"show":[203],"outperforms":[206],"existing":[207],"responses.":[213],"Visualization":[214],"analysis":[215],"shows":[216],"mutation":[219],"features":[220],"improves":[222],"prediction.":[228],"These":[229],"findings":[230],"confirm":[231],"powerful":[236],"tool":[237],"The":[243],"source":[244],"code":[245],"https://anonymous.4open.science/r/AFMCDR-DA65/.":[253]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}