Quantifying robustness of biochemical network models.

Lan Ma; Pablo A Iglesias

doi:10.1186/1471-2105-3-38

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Quantifying robustness of biochemical network models.

Lan Ma·Pablo A Iglesias

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Abstract

BACKGROUND: Robustness of mathematical models of biochemical networks is important for validation purposes and can be used as a means of selecting between different competing models. Tools for quantifying parametric robustness are needed. RESULTS: Two techniques for describing quantitatively the robustness of an oscillatory model were presented and contrasted. Single-parameter bifurcation analysis was used to evaluate the stability robustness of the limit cycle oscillation as well as the frequency and amplitude of oscillations. A tool from control engineering--the structural singular value (SSV)--was used to quantify robust stability of the limit cycle. Using SSV analysis, we find very poor robustness when the model's parameters are allowed to vary. CONCLUSION: The results show the usefulness of incorporating SSV analysis to single parameter sensitivity analysis to quantify robustness.

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Biochemical Phenomena Computational Biology Cyclic AMP Models, Biological Nonlinear Dynamics Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.Validation Study

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Lan Ma, Pablo A Iglesias. 2002-12-13. Quantifying robustness of biochemical network models.. https://doi.org/10.1186/1471-2105-3-38

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