Maximal extraction of biological information from genetic interaction data.

ABSTRACT: Extraction of all the biological information inherent in large-scale genetic interaction datasets remains a significant challenge for systems biology. The core problem is essentially that of classification of the relationships among phenotypes of mutant strains into biologically informative "rules" of gene interaction. Geneticists have determined such classifications based on insights from biological examples, but it is not clear that there is a systematic, unsupervised way to extract this information. In this paper we describe such a method that depends on maximizing a previously described context-dependent information measure to obtain maximally informative biological networks. We have successfully validated this method on two examples from yeast by demonstrating that more biological inf

SUBMITTER: Carter GW 

PROVIDER: S-EPMC2659753 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature