Apr 25, 2020

DriverGroup: A novel method for identifying drivergene groups

BioRxiv : the Preprint Server for Biology
V. V. H. PhamThuc Le

Abstract

Motivation: Identifying cancer driver genes is a key task in cancer informatics. Most existing methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesise that there are driver gene groups that work in concert to regulate cancer and we develop a novel computational method to detect those driver gene groups. Results: We develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (1) Constructing the gene network, (2) Discovering critical nodes of the constructed network, and (3) Identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify coding and non-coding driver groups for breast...Continue Reading

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Mentioned in this Paper

Study
Patterns
Entire Nervous System
Environment
Etiology
Nervous System Structure
Brain Function
Organism
Cellular Component Organization
Nervous system DRUGS

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