Encyclopedia of Systems Biology

2013 Edition
| Editors: Werner Dubitzky, Olaf Wolkenhauer, Kwang-Hyun Cho, Hiroki Yokota

Optimal Experimental Design, Model Discrimination

  • Brecht M. R. Donckels
Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-9863-7_1228


The problem of model discrimination arises when several models are proposed to describe one and the same process. To identify the best model from the set of rival models, it may be necessary to collect new information about the process, and thus, additional experiments have to be performed.

Optimal experimental design for model discrimination refers to the experimental design methodologies that are used to find the experimental conditions that allow to discriminate among rival models with the least experimental effort.


Model Discrimination

The aim of any modeling exercise is to obtain a  mathematical modelthat adequately describes and even predicts the process behavior. However, it is important to realize that lack of insight in the modeled process may result in the proposal of several so-called rival models, each of which represents a certain hypothesis of how the process works. The problem of identifying the best model from a set of rival models is...

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  1. Buzzi-Ferraris G, Forzatti P, Emig G, Hofmann H (1984) Sequential experimental design procedure for model discrimination in the case of multiple responses. Chem Eng Sci 39(1):81–85Google Scholar
  2. Donckels BMR, De Pauw DJW, De Baets B, Maertens J, Vanrolleghem PA (2009) An anticipatory approach to optimal experimental design for model discrimination. Chemometr Intell Lab Syst 95(1):53–63Google Scholar
  3. Hunter WG, Reiner AM (1965) Designs for discriminating between two rival models. Technometrics 5:307–323Google Scholar

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© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  1. 1.Department of Mathematical Modelling, Statistics and BioinformaticsGhent UniversityGhentBelgium