{"id":"https://openalex.org/W2030696948","doi":"https://doi.org/10.1186/1471-2105-10-165","title":"A joint finite mixture model for clustering genes from independent Gaussian and beta distributed data","display_name":"A joint finite mixture model for clustering genes from independent Gaussian and beta distributed data","publication_year":2009,"publication_date":"2009-05-29","ids":{"openalex":"https://openalex.org/W2030696948","doi":"https://doi.org/10.1186/1471-2105-10-165","mag":"2030696948","pmid":"https://pubmed.ncbi.nlm.nih.gov/19480678"},"language":"en","primary_location":{"id":"doi:10.1186/1471-2105-10-165","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1471-2105-10-165","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-10-165","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-10-165","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100720125","display_name":"Xiaofeng Dai","orcid":"https://orcid.org/0000-0002-0006-4042"},"institutions":[{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Xiaofeng Dai","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Tampere, Finland. xiaofeng.dai@tut.fi","[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Tampere, Finland. xiaofeng.dai@tut.fi","institution_ids":["https://openalex.org/I4210133110"]},{"raw_affiliation_string":"[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]","institution_ids":["https://openalex.org/I4210133110"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014044523","display_name":"Timo Erkkil\u00e4","orcid":null},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Timo Erkkil\u00e4","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Tampere, Finland","[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]},{"raw_affiliation_string":"[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]","institution_ids":["https://openalex.org/I4210133110"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026230936","display_name":"Olli Yli\u2010Harja","orcid":"https://orcid.org/0000-0001-8581-4414"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Olli Yli-Harja","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Tampere, Finland","[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]},{"raw_affiliation_string":"[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]","institution_ids":["https://openalex.org/I4210133110"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049442192","display_name":"Harri L\u00e4hdesm\u00e4ki","orcid":"https://orcid.org/0000-0002-0373-139X"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Harri L\u00e4hdesm\u00e4ki","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Tampere, Finland","[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]},{"raw_affiliation_string":"[Department of Signal Processing, Tampere University of Technology, Tampere, FINLAND]","institution_ids":["https://openalex.org/I4210133110"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049442192","https://openalex.org/A5100720125"],"corresponding_institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2072},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2072},"fwci":0.5477,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.66473567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"10","issue":"1","first_page":"165","last_page":"165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.5863000154495239,"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":0.5863000154495239,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.3571000099182129,"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":0.019300000742077827,"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":0.6523681879043579},{"id":"https://openalex.org/keywords/beta","display_name":"BETA (programming language)","score":0.5882716178894043},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.5257124304771423},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5238382816314697},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.48657143115997314},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4645891487598419},{"id":"https://openalex.org/keywords/dna-microarray","display_name":"DNA microarray","score":0.45187586545944214},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.43250715732574463},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.41786155104637146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4051494598388672},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3899303376674652},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.35299333930015564},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.33490824699401855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21407899260520935},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15430402755737305},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.141725093126297},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11488428711891174}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6523681879043579},{"id":"https://openalex.org/C2776174256","wikidata":"https://www.wikidata.org/wiki/Q830842","display_name":"BETA (programming language)","level":2,"score":0.5882716178894043},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.5257124304771423},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5238382816314697},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.48657143115997314},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4645891487598419},{"id":"https://openalex.org/C95371953","wikidata":"https://www.wikidata.org/wiki/Q591745","display_name":"DNA microarray","level":4,"score":0.45187586545944214},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.43250715732574463},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.41786155104637146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4051494598388672},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3899303376674652},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.35299333930015564},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.33490824699401855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21407899260520935},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15430402755737305},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.141725093126297},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11488428711891174},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","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":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D020869","descriptor_name":"Gene Expression Profiling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/1471-2105-10-165","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1471-2105-10-165","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-10-165","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:19480678","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19480678","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":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:doaj.org/article:72a9c740cb3b4ea9a62cba2eac619420","is_oa":true,"landing_page_url":"https://doaj.org/article/72a9c740cb3b4ea9a62cba2eac619420","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 10, Iss 1, p 165 (2009)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:2717092","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2717092","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/1471-2105-10-165","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1471-2105-10-165","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-10-165","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4334851996","display_name":null,"funder_award_id":"213462","funder_id":"https://openalex.org/F4320321108","funder_display_name":"Academy of Finland"}],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2030696948.pdf","grobid_xml":"https://content.openalex.org/works/W2030696948.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1571413698","https://openalex.org/W1579271636","https://openalex.org/W1981903823","https://openalex.org/W1982637996","https://openalex.org/W2009570821","https://openalex.org/W2011832962","https://openalex.org/W2043192125","https://openalex.org/W2063566427","https://openalex.org/W2072999024","https://openalex.org/W2082883083","https://openalex.org/W2098323244","https://openalex.org/W2120413242","https://openalex.org/W2122683221","https://openalex.org/W2126602684","https://openalex.org/W2141012957","https://openalex.org/W2142635246","https://openalex.org/W2151982307","https://openalex.org/W2162356875","https://openalex.org/W2168175751","https://openalex.org/W2169012810","https://openalex.org/W2488678869","https://openalex.org/W4249273120"],"related_works":["https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W1975321310","https://openalex.org/W2990323019","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W2095350775","https://openalex.org/W1996130883","https://openalex.org/W1578916557"],"abstract_inverted_index":{"BACKGROUND:":[0],"Cluster":[1,44],"analysis":[2,45],"has":[3,340],"become":[4],"a":[5,40,73,97,132,141,224,249,278],"standard":[6,215],"computational":[7],"method":[8,115],"for":[9,16,30,79,212,240],"gene":[10,303],"function":[11],"discovery":[12],"as":[13,15,63,67,96,172,193,307,315],"well":[14],"more":[17,142,198,324],"general":[18],"explanatory":[19],"data":[20,52,129,147,154,167,187,269,275,305],"analysis.":[21],"A":[22],"number":[23],"of":[24,34,66,100,126,145,209,291,331,337,344],"different":[25,36,128,153,274],"approaches":[26],"have":[27,189],"been":[28],"proposed":[29,91,113],"that":[31,151,188,271,320,346],"purpose,":[32],"out":[33],"which":[35,139,195,241,360],"mixture":[37,76,103,109,119,280],"models":[38],"provide":[39],"principled":[41],"probabilistic":[42,136],"framework.":[43,204],"is":[46],"increasingly":[47],"often":[48],"supplemented":[49],"with":[50,267,289,300,329],"multiple":[51,146],"sources":[53,59,148,155,168,276],"nowadays,":[54],"and":[55,86,106,134,179,223,227,258,310],"these":[56],"heterogeneous":[57],"information":[58,246,255],"should":[60],"be":[61,94,170,183,350,362],"made":[62],"efficient":[64,143],"use":[65,144],"possible.":[68],"RESULTS:":[69],"This":[70],"paper":[71],"presents":[72],"novel":[74],"Beta-Gaussian":[75],"model":[77,104,110,120,232,237,282],"(BGMM)":[78],"clustering":[80,203,286],"genes":[81,345],"based":[82,121],"on":[83],"Gaussian":[84,108,173,308],"distributed":[85,88,176],"beta":[87,102,175,316],"data.":[89],"The":[90,112],"BGMM":[92,114,158,321],"can":[93,169,181,322],"viewed":[95],"natural":[98],"extension":[99],"the":[101,107,214,231,244,253,259,285,367],"(BMM)":[105],"(GMM).":[111],"differs":[116],"from":[117],"other":[118,190],"methods":[122,150],"in":[123,352],"its":[124,292,332],"integration":[125],"two":[127,273,293,333],"types":[130,208],"into":[131,277],"single":[133,279],"unified":[135],"modeling":[137,163],"framework,":[138],"provides":[140,159],"than":[149],"analyze":[152],"separately.":[156],"Moreover,":[157],"an":[160,220],"exceedingly":[161],"flexible":[162],"framework":[164],"since":[165],"many":[166],"modeled":[171],"or":[174,297],"random":[177],"variables,":[178],"it":[180],"also":[182,318],"extended":[184],"to":[185,200,229,349,364],"integrate":[186],"parametric":[191],"distributions":[192],"well,":[194],"adds":[196],"even":[197],"flexibility":[199],"this":[201],"model-based":[202],"We":[205],"developed":[206],"three":[207,342],"estimation":[210],"algorithms":[211],"BGMM,":[213],"expectation":[216],"maximization":[217],"(EM)":[218],"algorithm,":[219],"approximated":[221],"EM":[222],"hybrid":[225],"EM,":[226],"propose":[228],"tackle":[230],"selection":[233,238],"problem":[234],"by":[235],"well-known":[236],"criteria,":[239],"we":[242],"test":[243],"Akaike":[245],"criterion":[247,256],"(AIC),":[248],"modified":[250],"AIC":[251],"(AIC3),":[252],"Bayesian":[254],"(BIC),":[257],"integrated":[260],"classification":[261],"likelihood-BIC":[262],"(ICL-BIC).":[263],"CONCLUSION:":[264],"Performance":[265],"tests":[266],"simulated":[268],"show":[270],"combining":[272],"joint":[281],"greatly":[283],"improves":[284],"accuracy":[287],"compared":[288,328],"either":[290,330],"extreme":[294,334],"cases,":[295],"GMM":[296],"BMM.":[298],"Applications":[299],"real":[301],"mouse":[302],"expression":[304],"(modeled":[306,314],"distribution)":[309,317],"protein-DNA":[311],"binding":[312],"probabilities":[313],"demonstrate":[319],"yield":[323],"biologically":[325],"reasonable":[326],"results":[327],"cases.":[335],"One":[336],"our":[338],"applications":[339],"found":[341],"groups":[343],"are":[347],"likely":[348],"involved":[351],"Myd88-dependent":[353],"Toll-like":[354],"receptor":[355],"3/4":[356],"(TLR-3/4)":[357],"signaling":[358],"cascades,":[359],"might":[361],"useful":[363],"better":[365],"understand":[366],"TLR-3/4":[368],"signal":[369],"transduction.":[370]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":3}],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2025-10-10T00:00:00"}