DomainRBF: a Bayesian regression approach to the prioritization of candidate domains for complex diseases.

ABSTRACT:

Background

Domains are basic units of proteins, and thus exploring associations between protein domains and human inherited diseases will greatly improve our understanding of the pathogenesis of human complex diseases and further benefit the medical prevention, diagnosis and treatment of these diseases. Within a given domain-domain interaction network, we make the assumption that similarities of disease phenotypes can be explained using proximities of domains associated with such diseases. Based on this assumption, we propose a Bayesian regression approach named "domainRBF" (domain Rank with Bayes Factor) to prioritize candidate domains for human complex diseases.

Results

Using a compiled dataset containing 1,614 associations between 671 domains and 1,145 disease phenotypes,

SUBMITTER: Zhang W 

PROVIDER: S-EPMC3108930 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature