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Logo of bmcsysbioBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Systems Biology
 
BMC Syst Biol. 2012; 6: 14.
Published online Mar 5, 2012. doi:  10.1186/1752-0509-6-14
PMCID: PMC3349553
Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
Irina Surovtsova,corresponding author1 Natalia Simus,1 Katrin Hübner,1 Sven Sahle,1 and Ursula Kummer1
1University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
corresponding authorCorresponding author.
Irina Surovtsova: irina.surovtsova/at/bioquant.uni-heidelberg.de; Natalia Simus: natalia.simus/at/bioquant.uni-heidelberg.de; Katrin Hübner: katrin.huebner/at/bioquant.uni-heidelberg.de; Sven Sahle: sven.sahle/at/bioquant.uni-heidelberg.de; Ursula Kummer: ursula.kummer/at/bioquant.uni-heidelberg.de
Received October 4, 2011; Accepted March 5, 2012.
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.
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