A Bayesian mixture model for partitioning gene expression data

Biometrics

Volumn 62, Issue 2, 2006, Pages 515-525

  Zhou, Chuan ^a   Wakefield, Jon ^b  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Bayesian hierarchical models; Birth death MCMC; Clustering; Microarrays; Mixture models

Indexed keywords

DATA HANDLING; HIERARCHICAL SYSTEMS; MARKOV PROCESSES; MICROARRAYS;

BAYESIAN; BAYESIAN HIERARCHICAL MODELLING; BAYESIAN MIXTURE MODELING; BIRTH-DEATH MCMC; CLUSTERINGS; CONVENTIONAL APPROACH; GENE EXPRESSION DATA; HIERARCHICAL MIXTURES; MIXTURE MODELING; PARTITIONING GENES;

GENE EXPRESSION;

ALGORITHM; BAYESIAN ANALYSIS; GENE EXPRESSION; HIERARCHICAL SYSTEM; MONTE CARLO ANALYSIS; RANDOM WALK METHOD; YEAST;

ARTICLE; BAYES THEOREM; BIRTH; DATA ANALYSIS; DEATH; FUNGAL GENE; GENE EXPRESSION; MATHEMATICAL MODEL; MEIOSIS; MONTE CARLO METHOD; NONHUMAN; NONPARAMETRIC TEST; PROBABILITY; YEAST;

SCHIZOSACCHAROMYCES POMBE;

EID: 33745283400     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2005.00492.x     Document Type: Article

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