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.