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ID: 230607.0, MPI für molekulare Genetik / Department of Vertebrate Genomics
Inferring dynamic properties of biochemical reaction networks from structural knowledge
Authors:Klipp, Edda; Liebermeister, Wolfram; Wierling, Christoph
Language:English
Date of Publication (YYYY-MM-DD):2004
Title of Journal:Genome Informatics Series: Proceedings of the Workshop on Genome Informatics
Journal Abbrev.:Genome Inform Ser Workshop Genome Inform
Volume:15
Issue / Number:1
Start Page:125
End Page:137
Review Status:not specified
Audience:Experts Only
Abstract / Description:Functional properties of biochemical networks depend on both the network structure and the kinetic parameters. Extensive data on metabolic network topologies have been collected in databases, but much less information is available about the kinetic constants or metabolite concentrations. Depending on the values of these parameters, metabolic fluxes and control coefficients may vary within a wide range. Nevertheless, some of the parameters may have little influence on the observables of interest. We address the question whether, despite uncertainty about kinetic parameters, probabilistic statements can be made about dynamic network features. To this end, we perform a variability analysis of the parameters: assuming that the parameters follow statistical distributions, we compute the resulting distributions of the network properties like metabolic fluxes, concentrations, or control coefficients by Monte Carlo simulation. In this manner, we study systematically the possible distributions arising from typical topologies of biochemical networks such as linear chains, branched networks, and signaling and gene expression cascades. This analysis reveals how much information about dynamic behavior can be drawn from structural knowledge.
External Publication Status:published
Document Type:Article
Communicated by:Hans Lehrach
Affiliations:MPI für molekulare Genetik
Identifiers:ISSN:0919-9454
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