{"id":"https://openalex.org/W4415400987","doi":"https://doi.org/10.1145/3728424.3760768","title":"PRESTIGE-ST: Patch Resolution and Encoder STrategies for Inference of Gene Expression from Spatial Transcriptomics","display_name":"PRESTIGE-ST: Patch Resolution and Encoder STrategies for Inference of Gene Expression from Spatial Transcriptomics","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415400987","doi":"https://doi.org/10.1145/3728424.3760768"},"language":null,"primary_location":{"id":"doi:10.1145/3728424.3760768","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728424.3760768","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Workshop on Multimedia Computing for Health and Medicine","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3728424.3760768","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041149430","display_name":"Maninder Kaur","orcid":"https://orcid.org/0000-0001-7602-5528"},"institutions":[{"id":"https://openalex.org/I119241673","display_name":"Indian Institute of Technology Ropar","ror":"https://ror.org/02qkhhn56","country_code":"IN","type":"education","lineage":["https://openalex.org/I119241673"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Maninder Kaur","raw_affiliation_strings":["Computer Science and Engineering, Indian Institute Of Technology Ropar, Ropar, India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Indian Institute Of Technology Ropar, Ropar, India","institution_ids":["https://openalex.org/I119241673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107640442","display_name":"Amit Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I119241673","display_name":"Indian Institute of Technology Ropar","ror":"https://ror.org/02qkhhn56","country_code":"IN","type":"education","lineage":["https://openalex.org/I119241673"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amit Kumar","raw_affiliation_strings":["Computer Science and Engineering, Indian Institute of Technology Ropar, Ropar, India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Indian Institute of Technology Ropar, Ropar, India","institution_ids":["https://openalex.org/I119241673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085527072","display_name":"Michele Ceccarelli","orcid":"https://orcid.org/0000-0002-4702-6617"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]},{"id":"https://openalex.org/I4210157065","display_name":"Sylvester Comprehensive Cancer Center","ror":"https://ror.org/0552r4b12","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I145608581","https://openalex.org/I4210101935","https://openalex.org/I4210157065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michele Ceccarelli","raw_affiliation_strings":["Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA"],"affiliations":[{"raw_affiliation_string":"Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA","institution_ids":["https://openalex.org/I4210157065","https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055826525","display_name":"Raghvendra Mall","orcid":"https://orcid.org/0000-0003-1779-3150"},"institutions":[{"id":"https://openalex.org/I4210115745","display_name":"Biogem","ror":"https://ror.org/01ymr5447","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I2801626668","https://openalex.org/I4210115745"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Raghvendra Mall","raw_affiliation_strings":["Genetiche 'G. Salvatore' Computational Biology Department, BIOGEM, Istituto di Ricerche, Ariano Irpino, Italy"],"affiliations":[{"raw_affiliation_string":"Genetiche 'G. Salvatore' Computational Biology Department, BIOGEM, Istituto di Ricerche, Ariano Irpino, Italy","institution_ids":["https://openalex.org/I4210115745"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078080109","display_name":"Sukrit Gupta","orcid":"https://orcid.org/0000-0002-8974-8482"},"institutions":[{"id":"https://openalex.org/I119241673","display_name":"Indian Institute of Technology Ropar","ror":"https://ror.org/02qkhhn56","country_code":"IN","type":"education","lineage":["https://openalex.org/I119241673"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sukrit Gupta","raw_affiliation_strings":["Biomedical Engineering and Artificial Intelligence and Data Engineering, Indian Institute of Technology Ropar, Ropar, India"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering and Artificial Intelligence and Data Engineering, Indian Institute of Technology Ropar, Ropar, India","institution_ids":["https://openalex.org/I119241673"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5041149430"],"corresponding_institution_ids":["https://openalex.org/I119241673"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28058973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"29","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9993000030517578,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9993000030517578,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9950000047683716,"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/T11970","display_name":"Molecular Biology Techniques and Applications","score":0.9868000149726868,"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/inference","display_name":"Inference","score":0.7099999785423279},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6474000215530396},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4429999887943268},{"id":"https://openalex.org/keywords/gene-expression-profiling","display_name":"Gene expression profiling","score":0.391400009393692},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.37310001254081726},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.36399999260902405},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.362199991941452},{"id":"https://openalex.org/keywords/transcriptome","display_name":"Transcriptome","score":0.34049999713897705},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.33480000495910645}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7099999785423279},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6499000191688538},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6474000215530396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.605400025844574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5357000231742859},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.4431000053882599},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4429999887943268},{"id":"https://openalex.org/C18431079","wikidata":"https://www.wikidata.org/wiki/Q1502169","display_name":"Gene expression profiling","level":4,"score":0.391400009393692},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.362199991941452},{"id":"https://openalex.org/C162317418","wikidata":"https://www.wikidata.org/wiki/Q252857","display_name":"Transcriptome","level":4,"score":0.34049999713897705},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.33480000495910645},{"id":"https://openalex.org/C145741570","wikidata":"https://www.wikidata.org/wiki/Q7251534","display_name":"Proteogenomics","level":5,"score":0.3249000012874603},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3181999921798706},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2962000072002411},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C105565629","wikidata":"https://www.wikidata.org/wiki/Q1248292","display_name":"Gene prediction","level":4,"score":0.28600001335144043},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C165864922","wikidata":"https://www.wikidata.org/wiki/Q411391","display_name":"Regulation of gene expression","level":3,"score":0.2563999891281128},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C2779733811","wikidata":"https://www.wikidata.org/wiki/Q5531562","display_name":"Gene signature","level":4,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3728424.3760768","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728424.3760768","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Workshop on Multimedia Computing for Health and Medicine","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3728424.3760768","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728424.3760768","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Workshop on Multimedia Computing for Health and Medicine","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2171461226","https://openalex.org/W2194775991","https://openalex.org/W2888113858","https://openalex.org/W2963446712","https://openalex.org/W3036882247","https://openalex.org/W3046305306","https://openalex.org/W3190202966","https://openalex.org/W3212609052","https://openalex.org/W3216067893","https://openalex.org/W4220897949","https://openalex.org/W4248172720","https://openalex.org/W4285803722","https://openalex.org/W4296693015","https://openalex.org/W4300862018","https://openalex.org/W4315786257","https://openalex.org/W4384283548","https://openalex.org/W4386031249","https://openalex.org/W4388539829","https://openalex.org/W4388539880","https://openalex.org/W4392874417","https://openalex.org/W4392947521","https://openalex.org/W4409086807"],"related_works":[],"abstract_inverted_index":{"Spatial":[0],"Transcriptomics":[1],"(ST)":[2],"integrates":[3],"histology":[4,48],"with":[5,129],"spatially":[6],"resolved":[7],"gene":[8,44,63,179,204],"expression,":[9,180],"offering":[10,174],"rich":[11],"insights":[12,187],"into":[13],"tissue":[14],"architecture":[15],"and":[16,21,31,91,107,152,194],"function.":[17],"However,":[18],"its":[19],"clinical":[20],"large-scale":[22],"deployment":[23],"is":[24,77,82],"hindered":[25],"by":[26,84],"high":[27],"costs,":[28],"technical":[29],"complexity,":[30],"limited":[32],"accessibility.":[33],"To":[34],"address":[35],"this,":[36],"computational":[37],"pathology":[38],"methods":[39],"have":[40,73],"emerged":[41],"to":[42,62],"predict":[43],"expression":[45,64,205],"directly":[46],"from":[47],"images,":[49],"typically":[50],"framing":[51],"the":[52,86,93,134,199],"task":[53],"as":[54],"a":[55,124],"multi-output":[56],"regression":[57],"problem":[58],"mapping":[59],"image":[60],"patches":[61,170],"profiles.":[65],"While":[66],"several":[67],"Convolutional":[68],"Neural":[69],"Network":[70],"(CNN)":[71],"models":[72,122,197],"been":[74],"proposed,":[75],"little":[76],"known":[78],"about":[79],"how":[80],"performance":[81,146],"influenced":[83],"(a)":[85],"number":[87],"of":[88,111,202],"trainable":[89],"parameters":[90],"(b)":[92],"patch":[94,131],"size":[95],"used":[96],"for":[97,155,182,191],"prediction.":[98,206],"Moreover,":[99],"existing":[100],"studies":[101],"rely":[102],"primarily":[103],"on":[104,133,147,168],"quantitative":[105],"metrics":[106],"overlook":[108],"biological":[109],"relevance":[110],"predictions.":[112],"In":[113],"this":[114],"study,":[115],"we":[116],"systematically":[117],"evaluated":[118],"multiple":[119],"convolution":[120],"based":[121,136],"(including":[123],"Vision":[125],"Transformer":[126],"(ViT)":[127],"model)":[128],"different":[130],"sizes":[132],"Xenium":[135],"Autoimmune":[137],"Machine":[138],"Learning":[139],"Challenge":[140],"(AMLC)":[141],"dataset.":[142],"We":[143],"assessed":[144],"model":[145],"both":[148],"globally":[149],"expressed":[150],"genes":[151],"subsets":[153],"enriched":[154],"immune":[156],"or":[157],"disease":[158],"associated":[159],"pathways.":[160],"Our":[161],"findings":[162],"reveal":[163],"that":[164],"compact":[165],"CNNs":[166],"trained":[167],"larger":[169],"outperform":[171],"deeper":[172],"models,":[173],"superior":[175],"accuracy":[176],"in":[177,198],"predicting":[178],"especially":[181],"biologically":[183,195],"important":[184],"genes.":[185],"These":[186],"provide":[188],"practical":[189],"guidance":[190],"designing":[192],"efficient":[193],"meaningful":[196],"emerging":[200],"field":[201],"image-based":[203]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-22T00:00:00"}