Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks.

ABSTRACT: Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of th

SUBMITTER: Brochado AR 

PROVIDER: S-EPMC3486866 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature