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Dataset Information

Gene prioritization in Type 2 Diabetes using domain interactions and network analysis.


ABSTRACT:

Background

Identification of disease genes for Type 2 Diabetes (T2D) by traditional methods has yielded limited success. Based on our previous observation that T2D may result from disturbed protein-protein interactions affected through disrupting modular domain interactions, here we have designed an approach to rank the candidates in the T2D linked genomic regions as plausible disease genes.

Results

Our approach integrates Weight value (Wv) method followed by prioritization using clustering coefficients derived from domain interaction network. Wv for each candidate is calculated based on the assumption that disease genes might be functionally related, mainly facilitated by interactions among domains of the interacting proteins. The benchmarking using a test dataset comprisin

SUBMITTER: Sharma A 

PROVIDER: S-EPMC2824729 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature