Model validation and robust stability analysis of the bacterial heat shock response using SOSTOOLS

Abstract

The complexity inherent in gene regulatory network models, as well as their nonlinear nature make them difficult to analyze or validate/invalidate using conventional tools. Combining ideas from robust control theory, real algebraic geometry, optimization and semi-definite programming, SOSTOOLS provides a promising framework to answer these robustness and model validation questions algorithmically. We adopt these tools in the study of the heat shock response in bacteria. For this purpose, we use a reduced order model of the bacterial heat stress response. We study the robust stability properties of this system to parametric uncertainty, and address the model validation/invalidation problem by proving the necessity for the existence of certain feedback loops to reproduce the known time behavior of the system.

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