TEAK: topology enrichment analysis framework for detecting activated biological subpathways.

ABSTRACT: To mine gene expression data sets effectively, analysis frameworks need to incorporate methods that identify intergenic relationships within enriched biologically relevant subpathways. For this purpose, we developed the Topology Enrichment Analysis frameworK (TEAK). TEAK employs a novel in-house algorithm and a tailor-made Clique Percolation Method to extract linear and nonlinear KEGG subpathways, respectively. TEAK scores subpathways using the Bayesian Information Criterion for context specific data and the Kullback-Leibler divergence for case-control data. In this article, we utilized TEAK with experimental studies to analyze microarray data sets profiling stress responses in the model eukaryote Saccharomyces cerevisiae. Using a public microarray data set, we identified via TEAK linear s

SUBMITTER: Judeh T 

PROVIDER: S-EPMC3561980 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature