A pan-cancer modular regulatory network analysis to identify common and cancer-specific network components.

ABSTRACT: Many human diseases including cancer are the result of perturbations to transcriptional regulatory networks that control context-specific expression of genes. A comparative approach across multiple cancer types is a powerful approach to illuminate the common and specific network features of this family of diseases. Recent efforts from The Cancer Genome Atlas (TCGA) have generated large collections of functional genomic data sets for multiple types of cancers. An emerging challenge is to devise computational approaches that systematically compare these genomic data sets across different cancer types that identify common and cancer-specific network components. We present a module- and network-based characterization of transcriptional patterns in six different cancers being studied in TCGA: b

SUBMITTER: Knaack SA 

PROVIDER: S-EPMC4213198 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature