A parameter estimation framework for kinetic models of biological systems [article]

Syed Murtuza Baker, Mangold, Michael, Prof. Dr., Schreiber, Falk, Prof. Dr., Junker, Björn H., Dr., Martin-Luther Universität, Universitäts- Und Landesbibliothek Sachsen-Anhalt
This thesis proposes a parameter estimation framework that has two modules, the parameter estimation module and the identifiability analysis module. The parameter estimation module contains a mathematically stable novel filtering technique named CSUKF that propagates the posterior probability distribution while satisfying the state constraints. It takes both the system and measurement noise into consideration. The identifiability analysis module composed of several data oriented submodules can
more » ... ted submodules can identify the non-identifiable parameters and can direct towards possible solutions. These submodules rank the parameters depending on their sensitivity towards model output, identifies both the structurally and practically non-identifiable parameters and can then direct towards possible solutions to this non-identifiability by suggesting possible extra measurements. If no extra measurement is possible then an informative prior is formulated based on subjective uncertainty which can then uniquely identify the parameters. The framework is applied successfully to three different biological models in order to estimate the parameters.
doi:10.25673/786 fatcat:2dzraekbbbe6jb7kfyi6c6nwzy