Nonlinear Filtering and Parameter Estimation for Complex Biological Systems

Abstract: Mathematical modeling plays an important role in studying complex biological systems and parameter estimation is an essential component of developing mathematical models. However, accurate estimation of parameters is conceptual and computational challenging as high fidelity models can contain a large number of parameters. Nonlinear filtering is one method that can be used to sequentially estimate both states and parameters. We shall examine the application of these filtering techniques on nonlinear models with varying sets of parameters.