Network topology-based detection of differential gene regulation and regulatory switches in cell metabolism and signaling.

ABSTRACT:

Background

Common approaches to pathway analysis treat pathways merely as lists of genes disregarding their topological structures, that is, ignoring the genes' interactions on which a pathway's cellular function depends. In contrast, PathWave has been developed for the analysis of high-throughput gene expression data that explicitly takes the topology of networks into account to identify both global dysregulation of and localized (switch-like) regulatory shifts within metabolic and signaling pathways. For this purpose, it applies adjusted wavelet transforms on optimized 2D grid representations of curated pathway maps.

Results

Here, we present the new version of PathWave with several substantial improvements including a new method for optimally mapping pathway networks unto

SUBMITTER: Piro RM 

PROVIDER: S-EPMC4031158 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature