Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data.

ABSTRACT:

Background

Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

Methods

In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Ill

SUBMITTER: de Matos Simoes R 

PROVIDER: S-EPMC4460634 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature