{"id":"https://openalex.org/W2579790009","doi":"https://doi.org/10.1109/bibm.2016.7822789","title":"Multivariate approach to the analysis of correlated RNA-seq data","display_name":"Multivariate approach to the analysis of correlated RNA-seq data","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2579790009","doi":"https://doi.org/10.1109/bibm.2016.7822789","mag":"2579790009"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2016.7822789","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2016.7822789","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5100328513","display_name":"Hyunjin Park","orcid":"https://orcid.org/0000-0001-5681-8918"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunjin Park","raw_affiliation_strings":["Department of Statistics, Seoul National University, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Seoul National University, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034909134","display_name":"Seungyeoun Lee","orcid":"https://orcid.org/0000-0001-7941-8933"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungyeoun Lee","raw_affiliation_strings":["Department of Mathematics and Statistics, Sejong University, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Sejong University, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101881868","display_name":"Ye Jin Kim","orcid":"https://orcid.org/0000-0002-9743-8513"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ye Jin Kim","raw_affiliation_strings":["Department of Food Science and Nutrition, Kyungpook National University, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Food Science and Nutrition, Kyungpook National University, Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031004025","display_name":"Myung\u2010Sook Choi","orcid":"https://orcid.org/0000-0002-6399-6787"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Myung-Sook Choi","raw_affiliation_strings":["Kyungpook National University, Daegu, Daegu, KR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University, Daegu, Daegu, KR","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100643662","display_name":"Taesung Park","orcid":"https://orcid.org/0000-0002-8294-590X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taesung Park","raw_affiliation_strings":["Department of Statistics, Seoul National University, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Seoul National University, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.10903707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1783","last_page":"1786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9986000061035156,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9986000061035156,"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":0.9908999800682068,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/multivariate-statistics","display_name":"Multivariate statistics","score":0.7492501139640808},{"id":"https://openalex.org/keywords/rna-seq","display_name":"RNA-Seq","score":0.7086498737335205},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.480753630399704},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.4687849283218384},{"id":"https://openalex.org/keywords/rna","display_name":"RNA","score":0.4543910622596741},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4211995601654053},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.2254164218902588},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.21951326727867126},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.19709256291389465},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15458625555038452},{"id":"https://openalex.org/keywords/transcriptome","display_name":"Transcriptome","score":0.13201552629470825},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.11475536227226257}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7492501139640808},{"id":"https://openalex.org/C107397762","wikidata":"https://www.wikidata.org/wiki/Q2542347","display_name":"RNA-Seq","level":5,"score":0.7086498737335205},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.480753630399704},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.4687849283218384},{"id":"https://openalex.org/C67705224","wikidata":"https://www.wikidata.org/wiki/Q11053","display_name":"RNA","level":3,"score":0.4543910622596741},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4211995601654053},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2254164218902588},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.21951326727867126},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.19709256291389465},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15458625555038452},{"id":"https://openalex.org/C162317418","wikidata":"https://www.wikidata.org/wiki/Q252857","display_name":"Transcriptome","level":4,"score":0.13201552629470825},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.11475536227226257}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2016.7822789","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2016.7822789","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1545338101","https://openalex.org/W1969885044","https://openalex.org/W1998329681","https://openalex.org/W2002374079","https://openalex.org/W2024683563","https://openalex.org/W2074414424","https://openalex.org/W2110065044","https://openalex.org/W2114104545","https://openalex.org/W2146512944","https://openalex.org/W2152239989","https://openalex.org/W2154431984","https://openalex.org/W4299507755","https://openalex.org/W4399607755","https://openalex.org/W6669607496","https://openalex.org/W6676591658"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W4394426846","https://openalex.org/W4200033037","https://openalex.org/W4394543623","https://openalex.org/W1991765889","https://openalex.org/W1990068454","https://openalex.org/W2472172556","https://openalex.org/W3213655218","https://openalex.org/W4394560977","https://openalex.org/W1570805059"],"abstract_inverted_index":{"High-throughput":[0],"RNA-seq":[1,24,50,59,78,98],"technology":[2],"has":[3,118],"emerged":[4],"as":[5],"a":[6,70],"powerful":[7],"tool":[8],"for":[9,37,103],"understanding":[10],"the":[11,39,54,82,91,125],"molecular":[12],"basis":[13],"of":[14,57,63,65,90,121],"phenotype":[15],"variation":[16],"in":[17],"biology,":[18],"including":[19],"disease.":[20],"Recently,":[21],"some":[22],"correlated":[23,49,58,77,97],"datasets":[25],"started":[26],"to":[27,61,73,95],"be":[28],"generated.":[29],"While":[30],"there":[31],"have":[32],"been":[33],"several":[34],"approaches":[35],"proposed":[36,92],"identifying":[38],"differentially":[40],"expressed":[41],"genes":[42],"(DEGs),":[43],"not":[44],"many":[45],"methods":[46],"can":[47],"analyze":[48],"data.":[51],"We":[52,68],"expect":[53],"simultaneous":[55],"analysis":[56,108],"data":[60,79,99,107],"increase":[62],"power":[64,120],"detecting":[66,122],"DEGs.":[67],"propose":[69],"multivariate":[71,116],"method":[72,93],"find":[74],"DEGs":[75,123],"on":[76,81],"based":[80],"Generalized":[83],"Estimating":[84],"Equations":[85],"(GEE)":[86],"approach.":[87],"The":[88],"advantage":[89],"is":[94],"consider":[96],"simultaneously":[100],"while":[101],"accounting":[102],"correlations.":[104],"Through":[105],"real":[106],"and":[109],"simulation":[110],"studies,":[111],"we":[112],"show":[113],"that":[114],"our":[115],"approach":[117],"higher":[119],"than":[124],"existing":[126],"methods.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
