title: Propagation of information in MetaNet graph models.
abstract: Information flow in metabolic networks has been studied with a graph model which represents the biochemical transformations occurring in the system under investigation. The "signal strength", an algebraic expression which estimates the probability that an intermediate metabolite is bound to a given enzyme, has been used to derive the "signal transmittance", the fraction of the informational signal at one intermediate that reaches another intermediate. The transmittance has been used to derive the "response ratio", the sensitivity of the rate of change of information at one metabolite consequent to a perturbation at another metabolite. Because the graphical representation corresponds to the biochemical events presumed to occur in the network, these quantities can be used to design experiments to confirm or falsify the hypotheses underlying the model and aid in understanding the regulatory properties of the system. The technique is illustrated by an example model, and its predictions are shown to be sensitive to modest structural changes in the network.
authors.affiliation: Statistics and Biomathematics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27710.
authors.forename: M C
authors.initials: MC
authors.lastname: Kohn
mesh_terms: D000818:Animals; D004798:Enzymes / Q000378:metabolism; D008660:Metabolism / Q000502:physiology*; D008954:Models, Biological
chemical_list: D004798:Enzymes