{"id":"https://openalex.org/W7126073193","doi":"https://doi.org/10.1109/bibm66473.2025.11357023","title":"A Dual-Graph-Driven Non-Negative Matrix Factorization Model for Single-Cell Omics Analysis","display_name":"A Dual-Graph-Driven Non-Negative Matrix Factorization Model for Single-Cell Omics Analysis","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126073193","doi":"https://doi.org/10.1109/bibm66473.2025.11357023"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5124199685","display_name":"Junjie Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junjie Lan","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China,510642"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China,510642","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123996238","display_name":"Nizhuan Wang","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":"Nizhuan Wang","raw_affiliation_strings":["Hong Kong Polytechnic University,Department of Chinese and Bilingual Studies,HongKong,China,100872"],"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University,Department of Chinese and Bilingual Studies,HongKong,China,100872","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124174281","display_name":"Jin Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Deng","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China,510642"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China,510642","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5124199685"],"corresponding_institution_ids":["https://openalex.org/I101479585"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67345355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1012","last_page":"1017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9958000183105469,"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":0.9958000183105469,"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":0.0010000000474974513,"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":0.0008999999845400453,"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/interpretability","display_name":"Interpretability","score":0.8385999798774719},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.6822999715805054},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6761000156402588},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6377999782562256},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46959999203681946},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.43320000171661377},{"id":"https://openalex.org/keywords/elastic-net-regularization","display_name":"Elastic net regularization","score":0.35109999775886536},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.35010001063346863},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.34769999980926514}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8385999798774719},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6822999715805054},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6783999800682068},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6761000156402588},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6377999782562256},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4925000071525574},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46959999203681946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636000096797943},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.43320000171661377},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.35109999775886536},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3434999883174896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3434000015258789},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.2955000102519989},{"id":"https://openalex.org/C189206191","wikidata":"https://www.wikidata.org/wiki/Q222046","display_name":"Genomics","level":4,"score":0.29109999537467957},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.27379998564720154},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2551000118255615},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.25450000166893005},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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":29,"referenced_works":["https://openalex.org/W1552434751","https://openalex.org/W1754857113","https://openalex.org/W2023887100","https://openalex.org/W2051658465","https://openalex.org/W2120205807","https://openalex.org/W2511896561","https://openalex.org/W3021145032","https://openalex.org/W3093858607","https://openalex.org/W3164692211","https://openalex.org/W3164839005","https://openalex.org/W3197108411","https://openalex.org/W4310601440","https://openalex.org/W4311232381","https://openalex.org/W4318612248","https://openalex.org/W4379521442","https://openalex.org/W4392393054","https://openalex.org/W4393252672","https://openalex.org/W4394743912","https://openalex.org/W4396801956","https://openalex.org/W4396954023","https://openalex.org/W4404814669","https://openalex.org/W4406259729","https://openalex.org/W4406580506","https://openalex.org/W4408312695","https://openalex.org/W4408537402","https://openalex.org/W4409486606","https://openalex.org/W4409882563","https://openalex.org/W4410603340","https://openalex.org/W4412152249"],"related_works":[],"abstract_inverted_index":{"The":[0,75,132],"advancement":[1],"of":[2,90,105,129,135],"single-cell":[3,27,35,72],"sequencing":[4,28,36],"technology":[5],"has":[6],"provided":[7],"unprecedented":[8],"resolution":[9],"for":[10,34,71],"investigating":[11],"cellular":[12],"heterogeneity.":[13],"Methods":[14],"based":[15],"on":[16,110],"non-negative":[17],"matrix":[18],"factorization":[19],"(NMF)":[20],"and":[21,45,94,102,118,126],"autoencoders":[22],"are":[23],"widely":[24],"applied":[25],"in":[26],"analysis.":[29,74],"However,":[30],"current":[31],"analytical":[32],"models":[33],"data":[37],"still":[38],"face":[39],"challenges":[40],"such":[41],"as":[42],"high":[43],"noise":[44],"limited":[46],"applicability":[47],"to":[48,52,98],"specific":[49],"scenarios,":[50],"leading":[51],"suboptimal":[53],"clustering":[54,100,124],"performance.":[55],"To":[56],"address":[57],"this":[58,60],"issue,":[59],"study":[61],"proposes":[62],"an":[63,84],"Autoencoder-like":[64],"Dual-Graph":[65],"Nonnegative":[66],"Matrix":[67],"Factorization":[68],"(ADGNMF)":[69],"model":[70],"multiomics":[73],"proposed":[76],"method":[77],"first":[78],"modifies":[79],"the":[80,106,130],"joint":[81],"NMF":[82],"into":[83],"autoencoder-like":[85],"architecture,":[86],"followed":[87],"by":[88],"construction":[89],"multi-omics":[91],"graph":[92,96],"regularization":[93,97],"co-cluster":[95],"enhance":[99],"performance":[101,125],"representational":[103],"capability":[104],"model.":[107,131],"Experimental":[108],"results":[109],"8":[111],"multi-source":[112],"transcriptomic":[113],"datasets,":[114,117],"2":[115,119],"transcriptomic-epigenomic":[116],"transcriptomic-proteomic":[120],"datasets":[121],"validate":[122],"superior":[123],"biological":[127],"interpretability":[128],"source":[133],"code":[134],"ADGNMF":[136],"is":[137],"available":[138],"at":[139],"https://github.com/jj-LanJADGNMF.":[140]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}
