{"id":"https://openalex.org/W7141056710","doi":"https://doi.org/10.48550/arxiv.2603.25247","title":"FEAST: Fully Connected Expressive Attention for Spatial Transcriptomics","display_name":"FEAST: Fully Connected Expressive Attention for Spatial Transcriptomics","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7141056710","doi":"https://doi.org/10.48550/arxiv.2603.25247"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25247","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25247","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25247","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130726977","display_name":"Taejin Jeong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeong, Taejin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022242031","display_name":"Joohyeok Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Joohyeok","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130748176","display_name":"Jinyeong Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jinyeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075621908","display_name":"Chanyoung Kim","orcid":"https://orcid.org/0000-0003-2749-8163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Chanyoung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5022991142","display_name":"Seong Jae Hwang","orcid":"https://orcid.org/0000-0002-3713-5553"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwang, Seong Jae","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.993399977684021,"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":0.993399977684021,"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":0.0012000000569969416,"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/T10885","display_name":"Gene expression and cancer classification","score":0.0007999999797903001,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.5921000242233276},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5113000273704529},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5101000070571899},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.49140000343322754},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.487199991941452},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.47769999504089355},{"id":"https://openalex.org/keywords/expressive-power","display_name":"Expressive power","score":0.376800000667572},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.37610000371932983},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.34869998693466187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7523999810218811},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5921000242233276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5824000239372253},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5113000273704529},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.47769999504089355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4422999918460846},{"id":"https://openalex.org/C195818886","wikidata":"https://www.wikidata.org/wiki/Q5421724","display_name":"Expressive power","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3767000138759613},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C2776800370","wikidata":"https://www.wikidata.org/wiki/Q5172864","display_name":"Correlative","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3091999888420105},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25247","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25247","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.25247","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25247","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spatial":[0,86],"Transcriptomics":[1],"(ST)":[2],"provides":[3],"spatially-resolved":[4],"gene":[5,30,182],"expression,":[6],"offering":[7],"crucial":[8],"insights":[9],"into":[10],"tissue":[11,49,94],"architecture":[12],"and":[13,120,194],"complex":[14,72],"diseases.":[15],"However,":[16],"its":[17],"prohibitive":[18],"cost":[19],"limits":[20],"widespread":[21],"adoption,":[22],"leading":[23],"to":[24,45,133,164],"significant":[25],"attention":[26,129,189],"on":[27,53,171],"inferring":[28],"spatial":[29],"expression":[31,183],"from":[32,59,138,158],"readily":[33],"available":[34,200],"whole":[35],"slide":[36],"images.":[37],"While":[38],"graph":[39],"neural":[40],"networks":[41],"have":[42],"been":[43],"proposed":[44],"model":[46,163],"interactions":[47],"between":[48],"regions,":[50,160],"their":[51],"reliance":[52],"pre-defined":[54],"sparse":[55],"graphs":[56],"prevents":[57],"them":[58],"considering":[60],"potentially":[61],"interacting":[62],"spot":[63,145],"pairs,":[64],"resulting":[65],"in":[66,70,143,181],"a":[67,96,166],"structural":[68],"limitation":[69],"capturing":[71,123],"biological":[73,110],"relationships.":[74],"To":[75,107],"address":[76],"this,":[77],"we":[78,112,148],"propose":[79],"FEAST":[80,177],"(Fully":[81],"connected":[82,98],"Expressive":[83],"Attention":[84],"for":[85],"Transcriptomics),":[87],"an":[88,150],"attention-based":[89],"framework":[90],"that":[91,127,154,176,191],"models":[92,117],"the":[93,101,135,162],"as":[95],"fully":[97],"graph,":[99],"enabling":[100],"consideration":[102],"of":[103],"all":[104],"pairwise":[105],"interactions.":[106,196],"better":[108],"reflect":[109],"interactions,":[111,122],"introduce":[113,149],"negative-aware":[114],"attention,":[115],"which":[116],"both":[118],"excitatory":[119],"inhibitory":[121],"essential":[124],"negative":[125,195],"relationships":[126],"standard":[128,144],"often":[130],"overlooks.":[131],"Furthermore,":[132],"mitigate":[134],"information":[136],"loss":[137],"truncated":[139],"or":[140],"ignored":[141],"context":[142],"image":[146],"extraction,":[147],"off-grid":[151],"sampling":[152],"strategy":[153],"gathers":[155],"additional":[156],"images":[157],"intermediate":[159],"allowing":[161],"capture":[165],"richer":[167],"morphological":[168],"context.":[169],"Experiments":[170],"public":[172],"ST":[173],"datasets":[174],"show":[175],"surpasses":[178],"state-of-the-art":[179],"methods":[180],"prediction":[184],"while":[185],"providing":[186],"biologically":[187],"plausible":[188],"maps":[190],"clarify":[192],"positive":[193],"Our":[197],"code":[198],"is":[199],"at":[201],"https://github.com/starforTJ/":[202],"FEAST.":[203]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-28T00:00:00"}
