A computational framework for the prioritization of disease-gene candidates.

ABSTRACT:

Background

The identification of genes and uncovering the role they play in diseases is an important and complex challenge. Genome-wide linkage and association studies have made advancements in identifying genetic variants that underpin human disease. An important challenge now is to identify meaningful disease-associated genes from a long list of candidate genes implicated by these analyses. The application of gene prioritization can enhance our understanding of disease mechanisms and aid in the discovery of drug targets. The integration of protein-protein interaction networks along with disease datasets and contextual information is an important tool in unraveling the molecular basis of diseases.

Results

In this paper we propose a computational pipeline for the prioritizat

SUBMITTER: Browne F 

PROVIDER: S-EPMC4547404 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature