The impact of multifunctional genes on "guilt by association" analysis.

ABSTRACT: Many previous studies have shown that by using variants of "guilt-by-association", gene function predictions can be made with very high statistical confidence. In these studies, it is assumed that the "associations" in the data (e.g., protein interaction partners) of a gene are necessary in establishing "guilt". In this paper we show that multifunctionality, rather than association, is a primary driver of gene function prediction. We first show that knowledge of the degree of multifunctionality alone can produce astonishingly strong performance when used as a predictor of gene function. We then demonstrate how multifunctionality is encoded in gene interaction data (such as protein interactions and coexpression networks) and how this can feed forward into gene function prediction algorithms

SUBMITTER: Gillis J 

PROVIDER: S-EPMC3041792 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature