Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset.

ABSTRACT:

Motivation

Identifying groups of co-regulated genes by monitoring their expression over various experimental conditions is complicated by the fact that such co-regulation is condition-specific. Ignoring the context-specific nature of co-regulation significantly reduces the ability of clustering procedures to detect co-expressed genes due to additional 'noise' introduced by non-informative measurements.

Results

We have developed a novel Bayesian hierarchical model and corresponding computational algorithms for clustering gene expression profiles across diverse experimental conditions and studies that accounts for context-specificity of gene expression patterns. The model is based on the Bayesian infinite mixtures framework and does not require a priori specification of the nu

SUBMITTER: Liu X 

PROVIDER: S-EPMC1617036 | biostudies-literature | 2006 Jul

REPOSITORIES: biostudies-literature