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Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics

Surovtsova, Irina ; Simus, Natalia ; Hübner, Katrin ; Sahle, Sven ; Kummer, Ursula

In: BMC Systems Biology, 6 (2012), Nr. 14. pp. 1-16. ISSN 1752-0509

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Download (1MB) | Lizenz: Creative Commons LizenzvertragSimplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics by Surovtsova, Irina ; Simus, Natalia ; Hübner, Katrin ; Sahle, Sven ; Kummer, Ursula underlies the terms of Creative Commons Attribution 3.0 Germany

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Abstract

Background: Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results: We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion: The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org.

Item Type: Article
Journal or Publication Title: BMC Systems Biology
Volume: 6
Number: 14
Publisher: BioMed Central
Place of Publication: London
Date Deposited: 17 Feb 2016 09:47
Date: 2012
ISSN: 1752-0509
Page Range: pp. 1-16
Faculties / Institutes: The Faculty of Bio Sciences > Dean's Office of the Faculty of Bio Sciences
Service facilities > Interdisciplinary Center for Scientific Computing
Service facilities > Bioquant
Service facilities > Cluster of Excellence Cellular Networks
Service facilities > Centre for Organismal Studies Heidelberg (COS)
Service facilities > Zentrum für Modellierung und Simulation in der Biowiss.
Subjects: 570 Life sciences
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