Dresden 2017 – wissenschaftliches Programm
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BP: Fachverband Biologische Physik
BP 4: Systems Biology & Gene Expression and Signalling
BP 4.4: Vortrag
Montag, 20. März 2017, 16:00–16:15, ZEU 250
Cause and Cure of Sloppiness in Ordinary Differential Equation Models — •Christian Tönsing1, Jens Timmer1,2,3, and Clemens Kreutz1,2 — 1Institute of Physics, University of Freiburg, Germany — 2Center for Biosystems Analysis (ZBSA), University of Freiburg, Germany — 3BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany
For the purpose of mathematical modeling of biochemical reaction networks by the frequently utilized nonlinear ordinary differential equation (ODE) models, parameter estimation and uncertainty analysis is a major task.
In this context the term sloppiness has been introduced recently for an unexpected characteristic of nonlinear ODE models. In particular, a broadened eigenvalue spectrum of the Hessian matrix of the objective function covering orders of magnitudes is observed, although no such hierarchy of parameter uncertainties was expected a priori.
In this work, it is shown that sloppiness originates from structures in the sensitivity matrix arising from the properties of the model topology and the experimental design. It will be clarified that the intensity of the sloppiness effect is controlled by the design of experiments, i.e., by the data. Thus, we conclude that the assignment of sloppiness to a model as a general characteristic is incomplete without discussing experimental design aspects. Furthermore, we validate this proposition by presenting strategies using optimal experimental design methods in order to circumvent the sloppiness issue and show results of non-sloppy designs for a benchmark model.