Friday, 11:00 - 11:25 h, Room: MA 376


Tanja Binder
Numerical optimization methods for significance analysis of parameters and subsets of metabolic networks

Coauthor: Ekaterina Kostina


We have developed an efficient numerical method, based on sensitivity analysis for parametric optimization problems, that can be used to identify the most important signaling pathways and the key parameters and variables in a mathematical model that is given by a system of ordinary differential equations. In the context of metabolic pathways, our approach can be used to guide experimental biologists in their choice which proteins they should measure. Mathematically, the problem results in the question how much improvement in terms of the cost function can be achieved by adding additional terms to the underlying dynamical model, i.e., whether these are to be included or not. The cost function describes the quality of the model response in comparison to process observations. After a parameter estimation for the simplest model, we can decide fast whether additional terms should be included in the model without having to re-optimize the enlarged models. We show the capability, reliability, and efficiency of our approach using complex problems from systems biology.


Talk 2 of the contributed session Fri.1.MA 376
"Model discrimination and experimental design" [...]
Cluster 12
"Life sciences & healthcare" [...]


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