Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics.

ABSTRACT:

Background

The demand for novel molecularly targeted drugs will continue to rise as we move forward toward the goal of personalizing cancer treatment to the molecular signature of individual tumors. However, the identification of targets and combinations of targets that can be safely and effectively modulated is one of the greatest challenges facing the drug discovery process. A promising approach is to use biological networks to prioritize targets based on their relative positions to one another, a property that affects their ability to maintain network integrity and propagate information-flow. Here, we introduce influence networks and demonstrate how they can be used to generate influence scores as a network-based metric to rank genes as potential drug targets.

Results

We

SUBMITTER: Penrod NM 

PROVIDER: S-EPMC3922430 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature