HiHMM: Bayesian non-parametric joint inference of chromatin state maps

Bioinformatics

Volumn 31, Issue 13, 2015, Pages 2066-2074

  Sohn, Kyung Ah ^a,b,c   Ho, Joshua W K ^d,e,f,g   Djordjevic, Djordje ^d,e   Jeong, Hyun Hwan ^a   Park, Peter J ^f,g   Kim, Ju Han ^b,c  

^a Ajou University   (South Korea)

^b Seoul National University College of Medicine   (South Korea)

^c Seoul National University   (South Korea)

^d VICTOR CHANG CARDIAC RESEARCH INSTITUTE   (Australia)

^e UNIVERSITY OF NEW SOUTH WALES   (Australia)

^f Harvard Medical School Center for Biomedical Informatics   (United States)

^g BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EUKARYOTA;

CHROMATIN; HISTONE;

ANIMAL; BAYES THEOREM; BIOLOGY; CHROMATIN; CHROMATIN IMMUNOPRECIPITATION; COMPUTER PROGRAM; DROSOPHILA MELANOGASTER; GENE EXPRESSION REGULATION; GENETICS; HUMAN; METABOLISM; NONPARAMETRIC TEST; PROCEDURES; PROMOTER REGION; REGULATORY SEQUENCE;

ANIMALS; BAYES THEOREM; CHROMATIN; CHROMATIN IMMUNOPRECIPITATION; COMPUTATIONAL BIOLOGY; DROSOPHILA MELANOGASTER; GENE EXPRESSION REGULATION, DEVELOPMENTAL; HISTONES; HUMANS; PROMOTER REGIONS, GENETIC; REGULATORY SEQUENCES, NUCLEIC ACID; SOFTWARE; STATISTICS, NONPARAMETRIC;

EID: 84936791924     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv117     Document Type: Article

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