{"id":"https://openalex.org/W7160276935","doi":"https://doi.org/10.1109/wacv61042.2026.00494","title":"Gene-DML: Dual-Pathway Multi-Level Discrimination for Gene Expression Prediction from Histopathology Images","display_name":"Gene-DML: Dual-Pathway Multi-Level Discrimination for Gene Expression Prediction from Histopathology Images","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160276935","doi":"https://doi.org/10.1109/wacv61042.2026.00494"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","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/A5111128651","display_name":"Yaxuan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yaxuan Song","raw_affiliation_strings":["The University of Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119272145","display_name":"Jianan Fan","orcid":"https://orcid.org/0000-0003-4424-9572"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jianan Fan","raw_affiliation_strings":["The University of Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135293440","display_name":"Hang Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hang Chang","raw_affiliation_strings":["Lawrence Berkeley National Laboratory,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lawrence Berkeley National Laboratory,USA","institution_ids":["https://openalex.org/I148283060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135284083","display_name":"Weidong Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Weidong Cai","raw_affiliation_strings":["The University of Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":37.0448,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.99355099,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"5090","last_page":"5099"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.2680000066757202,"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.2680000066757202,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.20630000531673431,"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/T10862","display_name":"AI in cancer detection","score":0.13220000267028809,"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/gene-expression","display_name":"Gene expression","score":0.4925000071525574},{"id":"https://openalex.org/keywords/histopathology","display_name":"Histopathology","score":0.41130000352859497},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.334199994802475},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.3264000117778778},{"id":"https://openalex.org/keywords/gene-expression-profiling","display_name":"Gene expression profiling","score":0.3027999997138977}],"concepts":[{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.4925000071525574},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.4562000036239624},{"id":"https://openalex.org/C544855455","wikidata":"https://www.wikidata.org/wiki/Q1070952","display_name":"Histopathology","level":2,"score":0.41130000352859497},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3084999918937683},{"id":"https://openalex.org/C18431079","wikidata":"https://www.wikidata.org/wiki/Q1502169","display_name":"Gene expression profiling","level":4,"score":0.3027999997138977},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.2973000109195709},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2928999960422516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.28519999980926514},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.2775000035762787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C153911025","wikidata":"https://www.wikidata.org/wiki/Q7202","display_name":"Molecular biology","level":1,"score":0.27079999446868896},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6406174898147583}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2042789810","https://openalex.org/W2471536144","https://openalex.org/W2805686747","https://openalex.org/W2809368942","https://openalex.org/W2923300855","https://openalex.org/W2963446712","https://openalex.org/W3036371598","https://openalex.org/W3036882247","https://openalex.org/W3166362230","https://openalex.org/W3176455777","https://openalex.org/W3188030217","https://openalex.org/W3190202966","https://openalex.org/W3200270857","https://openalex.org/W3205213119","https://openalex.org/W3217084439","https://openalex.org/W4284968770","https://openalex.org/W4285803722","https://openalex.org/W4310336097","https://openalex.org/W4312468136","https://openalex.org/W4319299885","https://openalex.org/W4386857835","https://openalex.org/W4392051226","https://openalex.org/W4392947521","https://openalex.org/W4402660143","https://openalex.org/W4403071574","https://openalex.org/W4403365602","https://openalex.org/W4403365647","https://openalex.org/W4403853489","https://openalex.org/W4404970811","https://openalex.org/W4409367396","https://openalex.org/W4413155147","https://openalex.org/W4415428547","https://openalex.org/W4415797639","https://openalex.org/W4416178267","https://openalex.org/W7133227398"],"related_works":[],"abstract_inverted_index":{"Accurately":[0],"predicting":[1],"gene":[2,38,92,162],"expression":[3,39,93,163],"from":[4],"histopathology":[5,35,82],"images":[6,36],"offers":[7],"a":[8,56],"scalable":[9],"and":[10,22,37,72,88,113,127,142,167],"non-invasive":[11],"approach":[12],"to":[13,67,133],"molecular":[14],"profiling,":[15],"with":[16,91],"significant":[17],"implications":[18],"for":[19],"precision":[20],"medicine":[21],"computational":[23],"pathology.":[24],"However,":[25],"existing":[26],"methods":[27],"often":[28],"underutilize":[29],"the":[30,101,119],"cross-modal":[31,136],"representation":[32],"alignment":[33,120],"between":[34,70,109],"profiles":[40],"across":[41,121,144],"multiple":[42],"representational":[43],"levels,":[44],"thereby":[45],"limiting":[46],"their":[47],"prediction":[48],"performance.":[49],"To":[50],"address":[51],"this,":[52],"we":[53],"propose":[54],"Gene-DML,":[55],"unified":[57],"framework":[58],"that":[59,156],"structures":[60],"latent":[61],"space":[62],"through":[63],"Dual-pathway":[64],"Multi-Level":[65],"discrimination":[66,78,104],"enhance":[68],"correspondence":[69],"morphological":[71],"transcriptional":[73],"modalities.":[74,122],"The":[75,165],"multi-scale":[76],"instance-level":[77],"pathway":[79,105],"aligns":[80],"hierarchical":[81],"representations":[83],"extracted":[84],"at":[85,172],"local,":[86],"neighbor,":[87],"global":[89],"levels":[90],"profiles,":[94],"capturing":[95],"scale-aware":[96],"morphological-transcriptional":[97],"relationships.":[98],"In":[99],"parallel,":[100],"cross-level":[102],"instance-group":[103],"enforces":[106],"structural":[107],"consistency":[108],"individual":[110],"(image/gene)":[111],"instances":[112],"modality-crossed":[114],"(gene/image,":[115],"respectively)":[116],"groups,":[117],"strengthening":[118],"By":[123],"jointly":[124],"modeling":[125],"fine-grained":[126],"structural-level":[128],"discrimination,":[129],"Gene-DML":[130,157],"is":[131],"able":[132],"learn":[134],"robust":[135],"representations,":[137],"enhancing":[138],"both":[139],"predictive":[140],"accuracy":[141],"generalization":[143],"diverse":[145],"biological":[146],"contexts.":[147],"Extensive":[148],"experiments":[149],"on":[150],"public":[151],"spatial":[152],"transcriptomics":[153],"datasets":[154,169],"demonstrate":[155],"achieves":[158],"state-of-the-art":[159],"performance":[160],"in":[161],"prediction.":[164],"code":[166],"processed":[168],"are":[170],"available":[171],"https://github.com/YXSong000/Gene-DML.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2026-05-06T00:00:00"}