Comparison of approaches for parameter identifiability analysis of biological systems

  • Motivation: Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of Systems Biology. The amount of experimental data that are used to build and calibrate these models is often limited. In this setting, the model parameters may not be uniquely determinable. Structural or a priori identifiability is a property of the system equations that indicates whether, in principle, the unknown model parameters can be determined from the available data. Results: We performed a case study using three current approaches for structural identifiability analysis for an application from cell biology. The approaches are conceptually different and are developed independently. The results of the three approaches are in agreement. We discuss strength and weaknesses of each of them and illustrate how they can be applied to real world problems.

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Metadaten
Author:Andreas RaueORCiDGND, Johan Karlsson, Maria Pia Saccomani, Mats Jirstrand, Jens Timmer
URN:urn:nbn:de:bvb:384-opus4-1132289
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/113228
ISSN:1367-4811OPAC
ISSN:1367-4803OPAC
Parent Title (English):Bioinformatics
Publisher:Oxford University Press (OUP)
Place of publication:Oxford
Type:Article
Language:English
Year of first Publication:2014
Publishing Institution:Universität Augsburg
Release Date:2024/06/03
Volume:30
Issue:10
First Page:1440
Last Page:1448
DOI:https://doi.org/10.1093/bioinformatics/btu006
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