Metabolic control analysis under uncertainty: framework development and case studies.

ABSTRACT: Information about the enzyme kinetics in a metabolic network will enable understanding of the function of the network and quantitative prediction of the network responses to genetic and environmental perturbations. Despite recent advances in experimental techniques, such information is limited and existing experimental data show extensive variation and they are based on in vitro experiments. In this article, we present a computational framework based on the well-established (log)linear formalism of metabolic control analysis. The framework employs a Monte Carlo sampling procedure to simulate the uncertainty in the kinetic data and applies statistical tools for the identification of the rate-limiting steps in metabolic networks. We applied the proposed framework to a branched biosynthetic p

SUBMITTER: Wang L 

PROVIDER: S-EPMC1304888 | biostudies-literature | 2004 Dec

REPOSITORIES: biostudies-literature