A Bayesian approach to the evolution of metabolic networks on a phylogeny.

ABSTRACT: The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a p

SUBMITTER: Mithani A 

PROVIDER: S-EPMC2917375 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature