Subset clustering of binary sequences, with an application to genomic abnormality data

Biometrics

Volumn 61, Issue 4, 2005, Pages 1027-1036

  Hoff, Peter D ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Genetic pathway; Multivariate binary data; Nonparametric Bayes; Unsupervised learning

Indexed keywords

BINARY SEQUENCES; GENES; POPULATION STATISTICS;

BINARY DATA; CLUSTERING APPROACH; CLUSTERINGS; DIRICHLET PROCESS MIXTURE MODEL; GENETIC PATHWAYS; GENOMICS; MODEL BASED APPROACH; MULTIVARIATE BINARY DATA; NON-PARAMETRIC BAYES; NUMBER OF CLUSTERS;

GENOME;

BIOMETRY; GENOME; MULTIVARIATE ANALYSIS; POPULATION GENETICS; STATISTICAL ANALYSIS;

ARTICLE; CARCINOGENESIS; GENE CLUSTER; GENETIC DISORDER; GENETIC PARAMETERS; LEARNING; MATHEMATICAL MODEL; MULTIVARIATE ANALYSIS; BIOLOGICAL MODEL; CHROMOSOME ABERRATION; CLUSTER ANALYSIS; GENETICS; GENOME; HUMAN; KIDNEY CARCINOMA; MONTE CARLO METHOD; PROBABILITY; STATISTICAL MODEL;

CARCINOMA, RENAL CELL; CHROMOSOME ABERRATIONS; CLUSTER ANALYSIS; GENOME, HUMAN; HUMANS; MARKOV CHAINS; MODELS, GENETIC; MODELS, STATISTICAL; MONTE CARLO METHOD;

EID: 33644863012     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2005.00381.x     Document Type: Article

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