Employing optimization and sensitivity analyses tools to generate and analyze mathematical models of T cell signaling events

Approaches using optimization and sensitivity analysis to generate and analyze mathematical models relating to T cell signaling are reviewed and extended. Two approaches to rationally evolve a mathematical model of the signaling events associated with T cell receptor engagement are compared: one relies upon expert knowledge and the other is directed by sensitivity analyses. Both approaches extensively employ optimization to address model structure and parametric uncertainty through exogenous inputs and parameter identification. In isolation, the sensitivity analyses driven approach failed to converge to a model interpretable within the context of known signaling pathway information. This work suggests that expert knowledge supplemented with sensitivity analyses results may effectively guide model evolution through use of constrained optimization techniques. These methods are equally applicable to other cellular types even though they are presented within the context of T lymphocytes.

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