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Metabolic network structure determines key aspects of functionality and regulation

Official URL:https://doi.org/10.1038/nature01166
PubMed:View item in PubMed
Creators Name:Stelling, J. and Klamt, S. and Bettenbrock, K. and Schuster, S. and Gilles, E.D.
Journal Title:Nature
Journal Abbreviation:Nature
Volume:420
Number:6912
Page Range:190-193
Date:14 November 2002
Keywords:Biomass, Cell Physiological Phenomena, Computational Biology, Computer Simulation, Energy Metabolism, Escherichia coli, Bacterial Gene Expression Regulation, Biological Models, Phenotype, Systems Theory
Abstract:The relationship between structure, function and regulation in complex cellular networks is a still largely open question. Systems biology aims to explain this relationship by combining experimental and theoretical approaches. Current theories have various strengths and shortcomings in providing an integrated, predictive description of cellular networks. Specifically, dynamic mathematical modelling of large-scale networks meets difficulties because the necessary mechanistic detail and kinetic parameters are rarely available. In contrast, structure-oriented analyses only require network topology, which is well known in many cases. Previous approaches of this type focus on network robustness or metabolic phenotype, but do not give predictions on cellular regulation. Here, we devise a theoretical method for simultaneously predicting key aspects of network functionality, robustness and gene regulation from network structure alone. This is achieved by determining and analysing the non-decomposable pathways able to operate coherently at steady state (elementary flux modes). We use the example of Escherichia coli central metabolism to illustrate the method.
ISSN:0028-0836
Publisher:Nature Publishing Group (U.K.)
Item Type:Article

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