{"id":"https://openalex.org/W7126068970","doi":"https://doi.org/10.1109/bibm66473.2025.11356593","title":"Fine-Grained Cross-Attention Between Drug Structures and Genes for Perturbation Prediction","display_name":"Fine-Grained Cross-Attention Between Drug Structures and Genes for Perturbation Prediction","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126068970","doi":"https://doi.org/10.1109/bibm66473.2025.11356593"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356593","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/A5124241190","display_name":"Hanwen Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanwen Lv","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University,Changsha,Hunan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124263417","display_name":"Yuting Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuting Bai","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University,Changsha,Hunan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121945908","display_name":"Jiawei Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Luo","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University,Changsha,Hunan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University,Changsha,Hunan,China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5124241190"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75573318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1783","last_page":"1786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.7685999870300293,"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":0.7685999870300293,"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":0.0364999994635582,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.0272000003606081,"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/overfitting","display_name":"Overfitting","score":0.8899000287055969},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.5052000284194946},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.4830000102519989},{"id":"https://openalex.org/keywords/drug-target","display_name":"Drug target","score":0.4702000021934509},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46480000019073486},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.45570001006126404},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4207000136375427},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.39629998803138733},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.36730000376701355}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8899000287055969},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.5666000247001648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5638999938964844},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49540001153945923},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46480000019073486},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.45570001006126404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43790000677108765},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4207000136375427},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.39629998803138733},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.34610000252723694},{"id":"https://openalex.org/C63222358","wikidata":"https://www.wikidata.org/wiki/Q6120337","display_name":"chEMBL","level":3,"score":0.3393999934196472},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.31040000915527344},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.28119999170303345},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C152662350","wikidata":"https://www.wikidata.org/wiki/Q815297","display_name":"Systems biology","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C165864922","wikidata":"https://www.wikidata.org/wiki/Q411391","display_name":"Regulation of gene expression","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C169822122","wikidata":"https://www.wikidata.org/wiki/Q230187","display_name":"Crosstalk","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.25929999351501465},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356593","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":[{"score":0.5572101473808289,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1812953419","display_name":null,"funder_award_id":"62372165,62032007","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":17,"referenced_works":["https://openalex.org/W2200017991","https://openalex.org/W2375821550","https://openalex.org/W2568779902","https://openalex.org/W2612467560","https://openalex.org/W2965552103","https://openalex.org/W2993905360","https://openalex.org/W3166542014","https://openalex.org/W4282036924","https://openalex.org/W4375955255","https://openalex.org/W4376226279","https://openalex.org/W4382631779","https://openalex.org/W4385245566","https://openalex.org/W4394919571","https://openalex.org/W4400140760","https://openalex.org/W4403784877","https://openalex.org/W4406017182","https://openalex.org/W4409364000"],"related_works":[],"abstract_inverted_index":{"Drug":[0],"perturbation":[1,115,141],"prediction":[2],"aims":[3],"to":[4,39,58,83,137],"accelerate":[5],"drug":[6,52,111,129],"target":[7],"discovery":[8],"by":[9,14],"simulating":[10],"transcriptional":[11],"responses":[12],"induced":[13],"chemical":[15],"interventions.":[16],"Although":[17],"deep":[18],"learning":[19],"methods":[20,65],"have":[21],"made":[22],"some":[23],"progress":[24],"in":[25],"this":[26],"field,":[27],"they":[28],"often":[29],"adopt":[30],"coarse-grained":[31],"linear":[32],"integration":[33],"strategies":[34],"(e.g.,":[35],"summation":[36],"or":[37],"concatenation)":[38],"integrate":[40],"a":[41,51,100,118],"single,":[42],"holistic":[43],"representation":[44],"of":[45,69,88],"the":[46,60,86,106,125],"gene":[47,79,114],"expression":[48],"profile":[49],"with":[50],"representation,":[53],"which":[54,73,134],"makes":[55],"it":[56],"difficult":[57],"capture":[59,139],"subtle":[61,140],"perturbations.":[62],"Furthermore,":[63],"these":[64,95],"are":[66],"predominantly":[67],"composed":[68],"Multi-Layer":[70],"Perceptrons":[71],"(MLPs),":[72],"cannot":[74],"dynamically":[75,121],"focus":[76],"on":[77,85,146],"key":[78],"features":[80],"and":[81,113,123,131,143],"tend":[82],"overfit":[84],"majority":[87],"genes":[89],"that":[90,155],"remain":[91],"unchanged.":[92],"To":[93],"address":[94],"challenges,":[96],"we":[97],"introduce":[98],"DGCAP,":[99],"novel":[101],"framework":[102],"specifically":[103],"designed":[104],"for":[105],"finegrained":[107],"modeling":[108],"relationships":[109],"between":[110,127],"structures":[112,130],"responses.":[116],"Crucially,":[117],"cross-attention":[119],"mechanism":[120],"identifies":[122],"weights":[124],"associations":[126],"specific":[128],"individual":[132],"genes,":[133],"enables":[135],"DGCAP":[136,156],"effectively":[138],"patterns":[142],"mitigate":[144],"overfitting":[145],"unchanged":[147],"genes.":[148],"Extensive":[149],"evaluations":[150],"across":[151],"diverse":[152],"datasets":[153],"indicate":[154],"outperforms":[157],"state-of-the-art":[158],"methods.":[159]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}