{"id":"https://openalex.org/W4294990955","doi":"https://doi.org/10.1093/bib/bbac398","title":"SCDD: a novel single-cell RNA-seq imputation method with diffusion and denoising","display_name":"SCDD: a novel single-cell RNA-seq imputation method with diffusion and denoising","publication_year":2022,"publication_date":"2022-09-01","ids":{"openalex":"https://openalex.org/W4294990955","doi":"https://doi.org/10.1093/bib/bbac398","pmid":"https://pubmed.ncbi.nlm.nih.gov/36070866"},"language":"en","primary_location":{"id":"doi:10.1093/bib/bbac398","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac398","pdf_url":null,"source":{"id":"https://openalex.org/S91767247","display_name":"Briefings in Bioinformatics","issn_l":"1467-5463","issn":["1467-5463","1477-4054"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"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/A5100414608","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0001-5516-0157"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Liu","raw_affiliation_strings":["College of Computer Science, Nankai University , Tianjin 300350 , China"],"raw_orcid":"https://orcid.org/0000-0001-5516-0157","affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University , Tianjin 300350 , China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038281654","display_name":"Yichen Pan","orcid":"https://orcid.org/0000-0002-4541-4261"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichen Pan","raw_affiliation_strings":["Centre for Bioinformatics and Intelligent Medicine, Nankai University , Tianjin 300350 , China","College of Computer Science, Nankai University , Tianjin 300350 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Bioinformatics and Intelligent Medicine, Nankai University , Tianjin 300350 , China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"College of Computer Science, Nankai University , Tianjin 300350 , China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072281138","display_name":"Zhihan Ruan","orcid":"https://orcid.org/0000-0002-2902-0852"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihan Ruan","raw_affiliation_strings":["Centre for Bioinformatics and Intelligent Medicine, Nankai University , Tianjin 300350 , China","College of Computer Science, Nankai University , Tianjin 300350 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Bioinformatics and Intelligent Medicine, Nankai University , Tianjin 300350 , China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"College of Computer Science, Nankai University , Tianjin 300350 , China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101554564","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0003-2643-6331"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Guo","raw_affiliation_strings":["College of Software, Northeastern University , Shenyang 110819 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Software, Northeastern University , Shenyang 110819 , China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100414608","https://openalex.org/A5101554564"],"corresponding_institution_ids":["https://openalex.org/I205237279","https://openalex.org/I9224756"],"apc_list":{"value":4011,"currency":"USD","value_usd":4011},"apc_paid":null,"fwci":0.9233,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.7246476,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"23","issue":"5","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":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/T10773","display_name":"Extracellular vesicles in disease","score":0.9516000151634216,"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":0.9463000297546387,"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/imputation","display_name":"Imputation (statistics)","score":0.8545879125595093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.694770872592926},{"id":"https://openalex.org/keywords/rna-seq","display_name":"RNA-Seq","score":0.5697495341300964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5251431465148926},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.43650758266448975},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.42368900775909424},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.41126951575279236},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38537082076072693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37290477752685547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2734605073928833},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.18367040157318115},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.13539952039718628},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.1199961006641388},{"id":"https://openalex.org/keywords/transcriptome","display_name":"Transcriptome","score":0.11105379462242126},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.11098948121070862},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.08141905069351196}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.8545879125595093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694770872592926},{"id":"https://openalex.org/C107397762","wikidata":"https://www.wikidata.org/wiki/Q2542347","display_name":"RNA-Seq","level":5,"score":0.5697495341300964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5251431465148926},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.43650758266448975},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.42368900775909424},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.41126951575279236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38537082076072693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37290477752685547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2734605073928833},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.18367040157318115},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.13539952039718628},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.1199961006641388},{"id":"https://openalex.org/C162317418","wikidata":"https://www.wikidata.org/wiki/Q252857","display_name":"Transcriptome","level":4,"score":0.11105379462242126},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.11098948121070862},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.08141905069351196}],"mesh":[{"descriptor_ui":"D000073359","descriptor_name":"Exome Sequencing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000073359","descriptor_name":"Exome Sequencing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000073359","descriptor_name":"Exome Sequencing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000081246","descriptor_name":"RNA-Seq","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000081246","descriptor_name":"RNA-Seq","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000081246","descriptor_name":"RNA-Seq","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D017423","descriptor_name":"Sequence Analysis, RNA","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D017423","descriptor_name":"Sequence Analysis, RNA","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D017423","descriptor_name":"Sequence Analysis, RNA","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D059010","descriptor_name":"Single-Cell Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D059010","descriptor_name":"Single-Cell Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D059010","descriptor_name":"Single-Cell Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1093/bib/bbac398","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bib/bbac398","pdf_url":null,"source":{"id":"https://openalex.org/S91767247","display_name":"Briefings in Bioinformatics","issn_l":"1467-5463","issn":["1467-5463","1477-4054"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in Bioinformatics","raw_type":"journal-article"},{"id":"pmid:36070866","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36070866","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Briefings in bioinformatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1711637756","display_name":null,"funder_award_id":"2021YFC2100801","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4210662038","display_name":"\u6d77\u91cf\u57fa\u56e0\u7ec4\u53d8\u5f02\u6570\u636e\u7ba1\u7406\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61872115","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4784360784","display_name":null,"funder_award_id":"2020YFA0908700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5569922501","display_name":null,"funder_award_id":"2021YFC2100800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6884513467","display_name":null,"funder_award_id":"2020YFA0908702","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1967327758","https://openalex.org/W2010653277","https://openalex.org/W2023887100","https://openalex.org/W2033072655","https://openalex.org/W2036193524","https://openalex.org/W2049633694","https://openalex.org/W2068881679","https://openalex.org/W2069089843","https://openalex.org/W2108169091","https://openalex.org/W2148203719","https://openalex.org/W2163605009","https://openalex.org/W2499952289","https://openalex.org/W2511896561","https://openalex.org/W2519887557","https://openalex.org/W2546514099","https://openalex.org/W2587062590","https://openalex.org/W2598326928","https://openalex.org/W2605810679","https://openalex.org/W2727913218","https://openalex.org/W2751468300","https://openalex.org/W2788837643","https://openalex.org/W2792693509","https://openalex.org/W2800392236","https://openalex.org/W2805619986","https://openalex.org/W2889326414","https://openalex.org/W2900308152","https://openalex.org/W2900510132","https://openalex.org/W2944189019","https://openalex.org/W2945823867","https://openalex.org/W2947877009","https://openalex.org/W2949067670","https://openalex.org/W2949272108","https://openalex.org/W2950372712","https://openalex.org/W2951217100","https://openalex.org/W2951381561","https://openalex.org/W2951506174","https://openalex.org/W2980495984","https://openalex.org/W3008081001","https://openalex.org/W3037216933","https://openalex.org/W3138479716","https://openalex.org/W3173253923","https://openalex.org/W3185008666","https://openalex.org/W4205559708","https://openalex.org/W4239026366","https://openalex.org/W6684191040","https://openalex.org/W6730084236"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W2782041652","https://openalex.org/W2612657834","https://openalex.org/W2392157706","https://openalex.org/W2599192953","https://openalex.org/W2952088488","https://openalex.org/W1521968289","https://openalex.org/W4225691210","https://openalex.org/W4399568863","https://openalex.org/W2792147139"],"abstract_inverted_index":{"Single-cell":[0],"sequencing":[1],"technologies":[2],"are":[3],"widely":[4],"used":[5],"to":[6,101,125],"discover":[7],"the":[8,12,21,42,54,84,92,103,109,136,141,145,157,163],"evolutionary":[9],"relationships":[10],"and":[11,120,139,160,172],"differences":[13],"in":[14,32,79],"cells.":[15],"Since":[16],"dropout":[17,99],"events":[18],"may":[19,46],"frustrate":[20],"analysis,":[22,169],"many":[23],"imputation":[24,37,78,89,105],"approaches":[25],"for":[26,53,74,97],"single-cell":[27,58,76,166],"RNA-seq":[28,59,77,167],"data":[29],"have":[30],"appeared":[31],"previous":[33,36],"attempts.":[34],"However,":[35],"attempts":[38],"usually":[39],"suffer":[40],"from":[41,132],"over-smooth":[43,158],"problem,":[44],"which":[45,133],"bring":[47],"limited":[48],"improvement":[49],"or":[50],"negative":[51],"effect":[52,164],"downstream":[55,168],"analysis":[56],"of":[57,94,129,165],"data.":[60],"To":[61],"solve":[62],"this":[63,80],"difficulty,":[64],"we":[65,134],"propose":[66],"a":[67,87,111],"novel":[68],"two-stage":[69],"diffusion-denoising":[70],"method":[71],"called":[72],"SCDD":[73,153],"large-scale":[75],"paper.":[81],"We":[82],"introduce":[83],"diffusion":[85],"i.e.":[86],"direct":[88],"strategy":[90],"using":[91],"expression":[93],"similar":[95,130],"cells":[96],"potential":[98],"sites,":[100],"perform":[102],"initial":[104],"at":[106],"first.":[107],"After":[108],"diffusion,":[110],"joint":[112],"model":[113],"integrated":[114],"with":[115],"graph":[116],"convolutional":[117],"neural":[118],"network":[119],"contractive":[121],"autoencoder":[122],"is":[123],"developed":[124],"generate":[126],"superposition":[127],"states":[128,138],"cells,":[131],"restore":[135],"original":[137],"remove":[140],"noise":[142],"introduced":[143],"by":[144],"diffusion.":[146],"The":[147],"final":[148],"experimental":[149],"results":[150],"indicate":[151],"that":[152],"could":[154],"effectively":[155],"suppress":[156],"problem":[159],"remarkably":[161],"improve":[162],"including":[170],"clustering":[171],"trajectory":[173],"analysis.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
