Context-sensitive network-based disease genetics prediction and its implications in drug discovery.

ABSTRACT:

Motivation

Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery.

Results

We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 node

SUBMITTER: Chen Y 

PROVIDER: S-EPMC5860178 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature