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Robustness analysis of biochemical network models

By Jongrae Kim, D.G. Bates, Ian Postlethwaite, L. Ma and P.A. Inglesias


Metadata only entryThis paper was published as IEE Proceedings on Systems Biology, 2006, 153 (3), pp.96-104. It is available from Doi: 10.1049/ip-syb:20050024Biological systems that have been experimentally verified to be robust to significant\ud changes in their environments require mathematical models that are themselves robust. In this\ud context, a necessary condition for model robustness is that the model dynamics should not be\ud sensitive to small variations in the model’s parameters. Robustness analysis problems of this\ud type have been extensively studied in the field of robust control theory and have been found to\ud be very difficult to solve in general. The authors describe how some tools from robust control\ud theory and nonlinear optimisation can be used to analyse the robustness of a recently proposed\ud model of the molecular network underlying adenosine 30,50-cyclic monophosphate (cAMP) oscillations\ud observed in fields of chemotactic Dictyostelium cells. The network model, which consists of\ud a system of seven coupled nonlinear differential equations, accurately reproduces the spontaneous\ud oscillations in cAMP observed during the early development of D. discoideum. The analysis by the\ud authors reveals, however, that very small variations in the model parameters can effectively destroy\ud the required oscillatory dynamics. A biological interpretation of the analysis results is that correct\ud functioning of a particular positive feedback loop in the proposed model is crucial to maintaining\ud the required oscillatory dynamics

Year: 2006
DOI identifier: 10.1049/ip-syb:20050024
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