Comparison of approaches for parameter identifiability analysis of biological systems.
BACKGROUND
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.


METHODS
For application of the approaches to further applications, code representations (DAISY, Mathematica and MATLAB) for benchmark model and data are provided on the authors webpage.


BACKGROUND
andreas.raue@fdm.uni-freiburg.de.
University of Freiburg, Institute for Physics, 79104 Freiburg, Germany, Merrimack Pharmaceuticals Inc., 02139 Cambridge, MA, USA, Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Göteborg, Sweden, Department of Information Engineering, University of Padova, 35131 Padova, Italy, BIOSS Centre for Biological Signalling Studies and Zentrum für Biosystemanalyse (ZBSA), University of Freiburg, 79104 Freiburg, Germany.
Andreas
A
Raue
Johan
J
Karlsson
Maria Pia
MP
Saccomani
Mats
M
Jirstrand
Jens
J
Timmer
D045744:Cell Line, Tumor; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D018793:Interleukin-13 / Q000494:pharmacology; D008223:Lymphoma / Q000235:genetics; D008954:Models, Biological; D012333:RNA, Messenger / Q000096:biosynthesis; D012107:Research Design; D049490:Systems Biology / Q000379:methods*
D018793:Interleukin-13; D012333:RNA, Messenger