Elucidation of Genetic Interactions in the Yeast GATA-Factor Network Using Bayesian Model Selection.

ABSTRACT: Understanding the structure and function of complex gene regulatory networks using classical genetic assays is an error-prone procedure that frequently generates ambiguous outcomes. Even some of the best-characterized gene networks contain interactions whose validity is not conclusively proven. Founded on dynamic experimental data, mechanistic mathematical models are able to offer detailed insights that would otherwise require prohibitively large numbers of genetic experiments. Here we attempt mechanistic modeling of the transcriptional network formed by the four GATA-factor proteins, a well-studied system of central importance for nitrogen-source regulation of transcription in the yeast Saccharomyces cerevisiae. To resolve ambiguities in the network organization, we encoded a set of five

SUBMITTER: Milias-Argeitis A 

PROVIDER: S-EPMC4788432 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature