Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data.

ABSTRACT:

Background

Cancer is a complex disease with a lucid etiology and in understanding the causation, we need to appreciate this complexity.

Objective

Here we are aiming to gain insights into the genetic associations of prostate cancer through a network-based systems approach using the BC3Net algorithm.

Methods

Specifically, we infer a prostate cancer Gene Regulatory Network (GRN) from a large-scale gene expression data set of 333 patient RNA-seq profiles obtained from The Cancer Genome Atlas (TCGA) database.

Results

We analyze the functional components of the inferred network by extracting subnetworks based on biological process information and interpret the role of known cancer genes within each process. Fur-thermore, we investigate the local landscape of prostate

SUBMITTER: Moore D 

PROVIDER: S-EPMC6446481 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature