Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

ABSTRACT: Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gen

SUBMITTER: Zhao J 

PROVIDER: S-EPMC3166320 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature