title: Reducing complexity in metabolic networks: making metabolic meshes manageable.
abstract: The dynamics of complex systems can be effectively analyzed by judicious use of intrinsic time constants. Order of magnitude estimation based on time constants has been used successfully to examine the dynamic behavior of complicated processes. The main goal of this paper is to introduce this approach to the analysis of complex metabolic systems. Time constants and dynamic modes of motion are defined within the context of well-established linear algebra. The order of magnitude estimation is then introduced into the systemic framework. The main goals of the analysis are: to provide improved understanding of biochemical dynamics and their physiological significance, and to yield reduced dynamic models that are physiologically realistic but tractable for practical use.
authors.forename: B O
authors.initials: BO
authors.lastname: Palsson
authors.forename: A
authors.initials: A
authors.lastname: Joshi
authors.forename: S S
authors.initials: SS
authors.lastname: Ozturk
mesh_terms: D000818:Animals; D003198:Computer Simulation; D004912:Erythrocytes / Q000378:metabolism; D004926:Escherichia coli / Q000254:growth & development; D008433:Mathematics; D008954:Models, Biological; D013997:Time Factors