{"id":"https://openalex.org/W7138433449","doi":"https://doi.org/10.1609/aaai.v40i9.37646","title":"Learning to Cluster Rare Cell Types: Implicit Semantic Data Augmentation for Spatial Multi-modal Omics Analysis","display_name":"Learning to Cluster Rare Cell Types: Implicit Semantic Data Augmentation for Spatial Multi-modal Omics Analysis","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138433449","doi":"https://doi.org/10.1609/aaai.v40i9.37646"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i9.37646","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37646","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37646/41608","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37646/41608","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045343174","display_name":"Daixian Liu","orcid":"https://orcid.org/0000-0002-9553-3453"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Daixian Liu","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125772439","display_name":"Hau-Sing So","orcid":null},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Hau-Sing So","raw_affiliation_strings":["University of Macau"],"affiliations":[{"raw_affiliation_string":"University of Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129689894","display_name":"Haoran Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I37574244","display_name":"Sichuan Agricultural University","ror":"https://ror.org/0388c3403","country_code":"CN","type":"education","lineage":["https://openalex.org/I37574244"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Chen","raw_affiliation_strings":["Sichuan Agricultural University"],"affiliations":[{"raw_affiliation_string":"Sichuan Agricultural University","institution_ids":["https://openalex.org/I37574244"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129645117","display_name":"Jiao Jiao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Li","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129655444","display_name":"Shanshan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Wang","raw_affiliation_strings":["Anhui University"],"affiliations":[{"raw_affiliation_string":"Anhui University","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129647476","display_name":"Mengzhu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengzhu Wang","raw_affiliation_strings":["Hebei University of Technology"],"affiliations":[{"raw_affiliation_string":"Hebei University of Technology","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129714518","display_name":"Jingcai Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jingcai Guo","raw_affiliation_strings":["The Hong Kong Polytechnic University"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5045343174"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78205128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"9","first_page":"7105","last_page":"7113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.875,"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":0.875,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.029400000348687172,"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":0.010599999688565731,"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/cluster-analysis","display_name":"Cluster analysis","score":0.5831000208854675},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5478000044822693},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.44350001215934753},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.42410001158714294},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4196999967098236},{"id":"https://openalex.org/keywords/data-driven","display_name":"Data-driven","score":0.40130001306533813},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.40130001306533813},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.35600000619888306},{"id":"https://openalex.org/keywords/biological-network","display_name":"Biological network","score":0.3481000065803528}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.723800003528595},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5831000208854675},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5478000044822693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46959999203681946},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41130000352859497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4097000062465668},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.40130001306533813},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.40130001306533813},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C2988382989","wikidata":"https://www.wikidata.org/wiki/Q370685","display_name":"Data space","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C152662350","wikidata":"https://www.wikidata.org/wiki/Q815297","display_name":"Systems biology","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C2986420190","wikidata":"https://www.wikidata.org/wiki/Q39045939","display_name":"Semantic space","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i9.37646","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37646","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37646/41608","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i9.37646","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i9.37646","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37646/41608","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.42228084802627563,"display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2082826544","display_name":null,"funder_award_id":"Postdoctoral","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3686789730","display_name":null,"funder_award_id":"62406100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5532155222","display_name":null,"funder_award_id":"Tianjin","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G5854786607","display_name":null,"funder_award_id":"Tianjin","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8863666567","display_name":null,"funder_award_id":"and No.","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"},{"id":"https://openalex.org/F4320323068","display_name":"Beijing Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138433449.pdf","grobid_xml":"https://content.openalex.org/works/W7138433449.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spatial":[0],"multi-modal":[1,114],"omics":[2,59,115],"technologies":[3],"have":[4,53],"transformed":[5],"biological":[6,157],"research":[7],"by":[8,66,84,133],"enabling":[9],"the":[10,67,129,175],"simultaneous":[11],"profiling":[12],"of":[13,69,178,182],"gene":[14],"expression,":[15],"protein":[16],"abundance,":[17],"and":[18,44,139,168,170,187],"chromatin":[19],"accessibility":[20],"within":[21],"their":[22,61],"native":[23],"spatial":[24,58,113],"contexts.":[25],"Despite":[26],"these":[27,89],"advances,":[28],"accurately":[29],"clustering":[30],"rare":[31,152],"cell":[32,153],"types":[33],"remains":[34],"a":[35,98],"major":[36],"challenge":[37],"due":[38],"to":[39,78,184],"data":[40],"sparsity,":[41],"high":[42],"dimensionality,":[43],"limited":[45],"annotated":[46],"samples.":[47],"While":[48],"Graph":[49],"Neural":[50],"Networks":[51],"(GNNs)":[52],"shown":[54],"potential":[55],"in":[56,128],"modeling":[57],"data,":[60],"effectiveness":[62],"is":[63],"often":[64],"constrained":[65],"use":[68],"fixed":[70],"K-nearest":[71],"neighbor":[72],"(KNN)":[73],"graph":[74,110],"structures,":[75],"which":[76],"fail":[77],"capture":[79],"latent":[80],"semantic":[81],"relationships":[82],"masked":[83],"sequencing":[85],"noise.":[86],"To":[87],"overcome":[88],"limitations,":[90],"we":[91],"propose":[92],"CRCT":[93,126],"(Clustering":[94],"Rare":[95],"Cell":[96],"Types):":[97],"novel":[99],"framework":[100],"that":[101,121],"combines":[102],"Implicit":[103],"Semantic":[104],"Data":[105],"Augmentation":[106],"(ISDA)":[107],"with":[108],"adaptive":[109],"learning":[111],"for":[112,151],"analysis.":[116],"Unlike":[117],"traditional":[118],"augmentation":[119,150],"strategies":[120],"generate":[122],"explicit":[123],"synthetic":[124,172],"samples,":[125],"operates":[127],"deep":[130],"feature":[131],"space":[132],"dynamically":[134],"estimating":[135],"intra-class":[136],"covariance":[137],"matrices":[138],"implicitly":[140],"perturbing":[141],"features":[142],"along":[143],"semantically":[144],"meaningful":[145],"directions.":[146],"This":[147],"enables":[148],"effective":[149],"populations":[154],"while":[155],"preserving":[156],"fidelity.":[158],"Extensive":[159],"experiments":[160],"across":[161],"four":[162],"real-world":[163],"datasets":[164],"(HLN,":[165],"MB,":[166],"Stereo\u2011CITE\u2011seq,":[167],"SPOTS)":[169],"one":[171],"benchmark":[173],"demonstrate":[174],"state-of-the-art":[176],"performance":[177],"CRCT,":[179],"achieving":[180],"improvements":[181],"up":[183],"+1.7":[185],"NMI":[186],"+7.8":[188],"ARI":[189],"over":[190],"strong":[191],"baseline":[192],"methods.":[193]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-03-18T00:00:00"}
