A novel network profiling analysis reveals system changes in epithelial-mesenchymal transition.

ABSTRACT: Patient-specific analysis of molecular networks is a promising strategy for making individual risk predictions and treatment decisions in cancer therapy. Although systems biology allows the gene network of a cell to be reconstructed from clinical gene expression data, traditional methods, such as bayesian networks, only provide an averaged network for all samples. Therefore, these methods cannot reveal patient-specific differences in molecular networks during cancer progression. In this study, we developed a novel statistical method called NetworkProfiler, which infers patient-specific gene regulatory networks for a specific clinical characteristic, such as cancer progression, from gene expression data of cancer patients. We applied NetworkProfiler to microarray gene expression data from 7

SUBMITTER: Shimamura T 

PROVIDER: S-EPMC3110206 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature