{"id":"https://openalex.org/W4390970582","doi":"https://doi.org/10.1109/bibm58861.2023.10385675","title":"Imputing single-cell RNA-seq data by graph autoencoder with multi-kernel","display_name":"Imputing single-cell RNA-seq data by graph autoencoder with multi-kernel","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390970582","doi":"https://doi.org/10.1109/bibm58861.2023.10385675"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385675","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bibm58861.2023.10385675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","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/A5102285805","display_name":"Kang Jiang","orcid":"https://orcid.org/0009-0002-5037-074X"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kang Jiang","raw_affiliation_strings":["University of Saskatchewan,Division of Biomedical Engineering,Saskatoon,Canada","Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Saskatchewan,Division of Biomedical Engineering,Saskatoon,Canada","institution_ids":["https://openalex.org/I32625721"]},{"raw_affiliation_string":"Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada","institution_ids":["https://openalex.org/I32625721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031510017","display_name":"Bo Liao","orcid":"https://orcid.org/0000-0002-3383-5691"},"institutions":[{"id":"https://openalex.org/I152033890","display_name":"Hainan Normal University","ror":"https://ror.org/031dhcv14","country_code":"CN","type":"education","lineage":["https://openalex.org/I152033890"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo. Liao","raw_affiliation_strings":["Hainan Normal University,School of Mathematics and Statistics,Haikou,China","School of Mathematics and Statistics, Hainan Normal University, Haikou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hainan Normal University,School of Mathematics and Statistics,Haikou,China","institution_ids":["https://openalex.org/I152033890"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Hainan Normal University, Haikou, China","institution_ids":["https://openalex.org/I152033890"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006758206","display_name":"P\u00e9tros Papagerakis","orcid":"https://orcid.org/0000-0001-9740-0593"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Petros Papagerakis","raw_affiliation_strings":["University of Saskatchewan,College of Dentistry,Saskatoon,Canada","College of Dentistry, University of Saskatchewan, Saskatoon, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Saskatchewan,College of Dentistry,Saskatoon,Canada","institution_ids":["https://openalex.org/I32625721"]},{"raw_affiliation_string":"College of Dentistry, University of Saskatchewan, Saskatoon, Canada","institution_ids":["https://openalex.org/I32625721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091157395","display_name":"Fang\u2010Xiang Wu","orcid":"https://orcid.org/0000-0002-4593-9332"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fang-Xiang Wu","raw_affiliation_strings":["University of Saskatchewan,Division of Biomedical Engineering,Department of Mechanical Engineering,Saskatoon,Canada","Department of Mechanical Engineering, Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Saskatchewan,Division of Biomedical Engineering,Department of Mechanical Engineering,Saskatoon,Canada","institution_ids":["https://openalex.org/I32625721"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada","institution_ids":["https://openalex.org/I32625721"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33325629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"228","last_page":"232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":1.0,"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":1.0,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9143999814987183,"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/T11313","display_name":"Immune cells in cancer","score":0.9142000079154968,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7053043842315674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6412639617919922},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4726414084434509},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4534667730331421},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4341302514076233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1576712727546692},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1508663296699524},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1135205626487732},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0584263801574707}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7053043842315674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6412639617919922},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4726414084434509},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4534667730331421},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4341302514076233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1576712727546692},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1508663296699524},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1135205626487732},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0584263801574707}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385675","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bibm58861.2023.10385675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1967327758","https://openalex.org/W2135937351","https://openalex.org/W2511896561","https://openalex.org/W2602582876","https://openalex.org/W2751468300","https://openalex.org/W2792693509","https://openalex.org/W2800392236","https://openalex.org/W2907783748","https://openalex.org/W2949067670","https://openalex.org/W2951217100","https://openalex.org/W2980495984","https://openalex.org/W2989747508","https://openalex.org/W3005127469","https://openalex.org/W3015184839","https://openalex.org/W3048858802","https://openalex.org/W3080162757","https://openalex.org/W3140605903","https://openalex.org/W3182503854","https://openalex.org/W4200227922","https://openalex.org/W4281628971","https://openalex.org/W4307348803","https://openalex.org/W4307407679","https://openalex.org/W4311474543","https://openalex.org/W4380369847"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W4220775285","https://openalex.org/W2891286602"],"abstract_inverted_index":{"Single-cell":[0],"RNA-sequencing":[1],"(scRNA-seq)":[2],"technology":[3],"has":[4],"revolutionized":[5],"the":[6,10,22,87,101],"field":[7],"by":[8,21,25],"enabling":[9],"profiling":[11],"of":[12,103,135],"transcriptomes":[13],"in":[14,34,133],"cell":[15],"resolution.":[16],"However,":[17],"it":[18],"is":[19],"flawed":[20],"sparsity":[23],"caused":[24],"low":[26],"mRNA":[27],"capture":[28],"efficiency":[29],"during":[30],"sequencing.":[31],"This":[32],"results":[33],"\"dropout\"":[35],"events":[36],"where":[37],"genes":[38],"are":[39],"expressed":[40,140],"but":[41],"not":[42],"detected.":[43],"Dropout":[44],"can":[45],"hinder":[46],"downstream":[47],"analyses":[48],"like":[49],"differential":[50],"expression":[51],"and":[52,70,122,138],"clustering.":[53],"To":[54,106],"tackle":[55],"this":[56],"issue,":[57],"we":[58,109],"present":[59],"a":[60,75,95],"novel":[61],"imputation":[62],"approach":[63],"called":[64],"MKGAE,":[65],"which":[66],"utilizes":[67],"graph":[68,97,113,116],"convolution":[69],"autoencoder":[71],"techniques":[72],"to":[73,100],"construct":[74],"generative":[76],"model":[77],"for":[78,115],"imputing":[79],"missing":[80],"values":[81],"within":[82],"scRNA-seq":[83,124],"data.":[84],"Meanwhile,":[85],"considering":[86],"intricate":[88],"relationships":[89],"between":[90],"genes,":[91],"merging":[92],"them":[93],"into":[94],"single":[96],"might":[98],"lead":[99],"loss":[102],"important":[104],"insights.":[105],"address":[107],"this,":[108],"utilize":[110],"two":[111],"gene-to-gene":[112],"kernels":[114],"convolution.":[117],"Experiments":[118],"across":[119],"both":[120],"simulated":[121],"real":[123],"datasets":[125],"illustrate":[126],"MKGAE\u2019s":[127],"superiority":[128],"over":[129],"other":[130],"state-of-the-art":[131],"methods":[132],"terms":[134],"clustering":[136],"analysis":[137],"differentially":[139],"gene":[141],"identification.":[142]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}