Accurate prediction of protein-protein interactions from sequence alignments using a Bayesian method.

ABSTRACT: Accurate and large-scale prediction of protein-protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interac

SUBMITTER: Burger L 

PROVIDER: S-EPMC2267735 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature