03.12.2009 Jens Timmer "Identifiability Analysis and Experimental Design for Dynamical Models in Systems Biology"
Mathematical models of the dynamics of cellular processes promise to yield new insights into the underlying biology and their systems' properties. Since the processes are usually high-dimensional and time-resolved experimental data of the processes are sparse, parameter estimation faces the challenges of structural and practical non-identifiability of the parameters. Non-identifiability induces non-observability. Non-observability reduces the predictive power of the models. We will discuss a new approach that allows for identifiability and observability analysis. We demonstrate how identifiability analysis combined with observability analysis supports the iterative cycle between modelling and experimentation in systems biology.