{"id":"https://openalex.org/W7165166342","doi":"https://doi.org/10.48550/arxiv.2606.18672","title":"scGTN: Deep Siamese Graph Transformer Network for Single-cell RNA Sequencing Clustering","display_name":"scGTN: Deep Siamese Graph Transformer Network for Single-cell RNA Sequencing Clustering","publication_year":2026,"publication_date":"2026-06-17","ids":{"openalex":"https://openalex.org/W7165166342","doi":"https://doi.org/10.48550/arxiv.2606.18672"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.18672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18672","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.2606.18672","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043229661","display_name":"Jinke Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jinke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138869359","display_name":"Yifan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138941325","display_name":"Siyu Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi, Siyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026439520","display_name":"Caiyang Yu","orcid":"https://orcid.org/0000-0001-8246-1561"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Caiyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052483692","display_name":"Ziyue Qiao","orcid":"https://orcid.org/0000-0002-9485-4861"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiao, Ziyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138831637","display_name":"Nan Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Nan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138882466","display_name":"Jiancheng Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv, Jiancheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102822750","display_name":"Wei Ju","orcid":"https://orcid.org/0000-0003-3548-8651"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ju, Wei","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":0.9955000281333923,"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":0.9955000281333923,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0012000000569969416,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","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/cluster-analysis","display_name":"Cluster analysis","score":0.6873999834060669},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5332000255584717},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4821999967098236},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.38600000739097595},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.35839998722076416},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.3538999855518341},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.35179999470710754},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.326200008392334}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6873999834060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6424999833106995},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5332000255584717},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4821999967098236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4578000009059906},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.4253000020980835},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.38600000739097595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37779998779296875},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.3538999855518341},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34040001034736633},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.326200008392334},{"id":"https://openalex.org/C28225019","wikidata":"https://www.wikidata.org/wiki/Q4915005","display_name":"Biological network","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C32276052","wikidata":"https://www.wikidata.org/wiki/Q908349","display_name":"Motif (music)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C67705224","wikidata":"https://www.wikidata.org/wiki/Q11053","display_name":"RNA","level":3,"score":0.2515999972820282},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.18672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18672","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.2606.18672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18672","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Single-cell":[0],"RNA":[1],"sequencing":[2],"(scRNA-seq)":[3],"serves":[4],"a":[5,68,102,121,156],"pivotal":[6],"role":[7],"in":[8,33,57,63,155],"characterizing":[9],"gene":[10,85],"expression":[11,86],"at":[12,178],"the":[13,17,24,30,44,51,152],"cellular":[14,27],"level,":[15],"enabling":[16],"identification":[18],"of":[19,26],"cell":[20,93,153],"types":[21],"and":[22,46,88,104,133],"advancing":[23],"understanding":[25],"heterogeneity.":[28],"Despite":[29],"significant":[31],"progress":[32],"scRNA-seq":[34,58,99,164],"data":[35,100],"clustering,":[36],"we":[37,66,97,144],"argue":[38],"that":[39,110,167],"current":[40],"methods":[41],"always":[42],"ignore":[43],"sparsity":[45],"noise,":[47],"as":[48,50,101,112],"well":[49],"complex":[52],"intercellular":[53,89,118],"structural":[54,90,139],"information":[55,132],"inherent":[56],"data.":[59],"Toward":[60],"this":[61,64],"end,":[62],"paper,":[65],"propose":[67],"novel":[69],"single-cell":[70],"RNA-seq":[71],"clustering":[72,154],"framework":[73],"via":[74],"deep":[75],"Siamese":[76,122],"Graph":[77],"Transformer":[78],"Network":[79],"(termed":[80],"scGTN),":[81],"which":[82],"explicitly":[83,129],"integrates":[84],"profile":[87],"dependencies":[91],"for":[92,136],"clustering.":[94],"In":[95],"particular,":[96],"formulate":[98],"graph":[103,108,123],"construct":[105],"two":[106],"augmented":[107],"views":[109,114],"serve":[111],"dual":[113],"to":[115,128,150],"capture":[116],"complementary":[117],"information.":[119],"Then,":[120],"transformer":[124],"network":[125],"is":[126,176],"employed":[127],"incorporate":[130],"shortest-path":[131],"node-wise":[134],"distances":[135],"capturing":[137],"richer":[138],"relationships":[140],"between":[141],"cells.":[142],"Finally,":[143],"employ":[145],"an":[146],"optimal":[147],"transport":[148],"strategy":[149],"guide":[151],"self-supervised":[157],"manner.":[158],"Extensive":[159],"experiments":[160],"on":[161],"multiple":[162],"benchmark":[163],"datasets":[165],"demonstrate":[166],"our":[168],"scGTN":[169],"consistently":[170],"outperforms":[171],"existing":[172],"methods.":[173],"Our":[174],"code":[175],"available":[177],"https://github.com/W-RMSL/scGTN.":[179]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-19T00:00:00"}