Identifiability and observability analysis for experimental design in nonlinear dynamical models
- Dynamical models of cellular processes promise to yield new insights into the underlying systems and their biological interpretation. The processes are usually nonlinear, high dimensional, and time-resolved experimental data of the processes are sparse. Therefore, parameter estimation faces the challenges of structural and practical nonidentifiability. Nonidentifiability of parameters induces nonobservability of trajectories, reducing the predictive power of the model. We will discuss a generic approach for nonlinear models that allows for identifiability and observability analysis by means of a realistic example from systems biology. The results will be utilized to design new experiments that enhance model predictiveness, illustrating the iterative cycle between modeling and experimentation in systems biology.
| Author: | Andreas RaueORCiDGND, V. Becker, U. Klingmüller, J. Timmer |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1132718 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/113271 |
| ISSN: | 1054-1500OPAC |
| ISSN: | 1089-7682OPAC |
| Parent Title (English): | Chaos: An Interdisciplinary Journal of Nonlinear Science |
| Publisher: | AIP Publishing |
| Type: | Article |
| Language: | English |
| Year of first Publication: | 2010 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2024/06/03 |
| Volume: | 20 |
| Issue: | 4 |
| First Page: | 045105 |
| DOI: | https://doi.org/10.1063/1.3528102 |
| Institutes: | Fakultät für Angewandte Informatik |
| Fakultät für Angewandte Informatik / Institut für Informatik | |
| Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Modellierung und Simulation biologischer Prozesse | |
| Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
| Licence (German): |  Deutsches Urheberrecht |
