kim1

Title

Robustness analysis of biochemical network models

Authors

J. Kim (1), D.G. Bates (1), I. Postlethwaite (1), L. Ma (2) and P.A. Iglesias (3)

Affiliations

1. Control and Instrumentation Group, Department of Engineering, University of Leicester, Leicester LE1 7RH, UK 2.Green Center Division for Systems Biology, Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, TX, USA 3. Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA

Abstract

Biological systems that have been experimentally verified to be robust to significant changes in their environments require mathematical models that are themselves robust. In this context, a necessary condition for model robustness is that the model dynamics should not be sensitive to small variations in the model's parameters. Robustness analysis problems of this type have been extensively studied in the field of robust control theory and have been found to be very difficult to solve in general. The authors describe how some tools from robust control theory and nonlinear optimisation can be used to analyse the robustness of a recently proposed model of the molecular network underlying adenosine 30,50-cyclic monophosphate (cAMP) oscillations observed in fields of chemotactic Dictyostelium cells. The network model, which consists of a system of seven coupled nonlinear differential equations, accurately reproduces the spontaneous oscillations in cAMP observed during the early development of D. discoideum. The analysis by the authors reveals, however, that very small variations in the model parameters can effectively destroy the required oscillatory dynamics. A biological interpretation of the analysis results is that correct functioning of a particular positive feedback loop in the proposed model is crucial to maintaining the required oscillatory dynamics.

Journal

IEE Proc.-Syst. Biol., Vol. 153, No. 3, May 2006

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