title: Systematic construction of kinetic models from genome-scale metabolic networks.
abstract: The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.
authors: School of Computer Science, Manchester Centre for Integrative Systems Biology, University of Manchester, Manchester, United Kingdom.
authors: Natalie J
authors: NJ
authors: Stanford
authors: Timo
authors: T
authors: Lubitz
authors: Kieran
authors: K
authors: Smallbone
authors: Edda
authors: E
authors: Klipp
authors: Pedro
authors: P
authors: Mendes
authors: Wolfram
authors: W
authors: Liebermeister
mesh_terms: D016678:Genome; D007700:Kinetics; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D013816:Thermodynamics