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Bioinformatics Advance Access originally published online on June 8, 2009
Bioinformatics 2009 25(15):1923-1929; doi:10.1093/bioinformatics/btp358
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood

A. Raue 1,*, C. Kreutz 1, T. Maiwald 2, J. Bachmann 3, M. Schilling 3, U. Klingmüller 3 and J. Timmer 1,4

1 Physics Institute, University of Freiburg, 79104 Freiburg, Germany, 2 Department of Systems Biology, Harvard Medical School, 02115 Boston, MA, USA, 3 Division of Systems Biology of Signal Transduction, DKFZ-ZMBH Alliance, German Cancer Research Center, 69120 Heidelberg and 4 Freiburg Institute for Advanced Studies, University of Freiburg, 79104 Freiburg, Germany

* To whom correspondence should be addressed.


  Abstract

Motivation: Mathematical description of biological reaction networks by differential equations leads to large models whose parameters are calibrated in order to optimally explain experimental data. Often only parts of the model can be observed directly. Given a model that sufficiently describes the measured data, it is important to infer how well model parameters are determined by the amount and quality of experimental data. This knowledge is essential for further investigation of model predictions. For this reason a major topic in modeling is identifiability analysis.

Results: We suggest an approach that exploits the profile likelihood. It enables to detect structural non-identifiabilities, which manifest in functionally related model parameters. Furthermore, practical non-identifiabilities are detected, that might arise due to limited amount and quality of experimental data. Last but not least confidence intervals can be derived. The results are easy to interpret and can be used for experimental planning and for model reduction.

Availability: An implementation is freely available for MATLAB and the PottersWheel modeling toolbox at http://web.me.com/andreas.raue/profile/software.html.

Contact: andreas.raue{at}me.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Martin Bishop

Received on April 14, 2009; revised on May 21, 2009; accepted on June 3, 2009

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