Integration of metabolome data with metabolic networks reveals reporter reactions.

ABSTRACT: Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to m

SUBMITTER: Cakir T 

PROVIDER: S-EPMC1682015 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature