Discover the molecular biomarker associated with cell death and extracellular matrix module in ovarian cancer.

ABSTRACT: High throughput technologies have provided many new research methods for ovarian cancer investigation. In tradition, in order to find the underlying functional mechanisms of the survival-associated genes, gene sets enrichment analysis (GSEA) is always regarded as the important choice. However, GSEA produces too many candidate genes and cannot discover the signaling transduction cascades. In this work, we have used a network-based strategy to optimize the discovery of biomarkers using multifactorial data, including patient expression, clinical survival, and protein-protein interaction (PPI) data. The biomarkers discovered by this strategy belong to the network-based biomarker, which is apt to reveal the underlying functional mechanisms of the biomarker. In this work, over 400 expression arr

SUBMITTER: Liu Q 

PROVIDER: S-EPMC4378326 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature