A method for zooming of nonlinear models of biochemical systems
Open Access
- 1 January 2011
- journal article
- research article
- Published by Springer Nature in BMC Systems Biology
- Vol. 5 (1) , 140
Abstract
Models of biochemical systems are typically complex, which may complicate the discovery of cardinal biochemical principles. It is therefore important to single out the parts of a model that are essential for the function of the system, so that the remaining non-essential parts can be eliminated. However, each component of a mechanistic model has a clear biochemical interpretation, and it is desirable to conserve as much of this interpretability as possible in the reduction process. Furthermore, it is of great advantage if we can translate predictions from the reduced model to the original model.Keywords
This publication has 37 references indexed in Scilit:
- Mass and Information Feedbacks through Receptor Endocytosis Govern Insulin Signaling as Revealed Using a Parameter-free Modeling FrameworkJournal of Biological Chemistry, 2010
- Zooming of states and parameters using a lumping approach including back-translationBMC Systems Biology, 2010
- Robust simplifications of multiscale biochemical networksBMC Systems Biology, 2008
- Exact model reduction of combinatorial reaction networksBMC Systems Biology, 2008
- Structural robustness of biochemical network models-with application to the oscillatory metabolism of activated neutrophilsIET Systems Biology, 2008
- Reduced modeling of signal transduction – a modular approachBMC Bioinformatics, 2007
- Use and abuse of the quasi-steady-state approximationSystems Biology, 2006
- Systems Biology Toolbox for MATLAB: a computational platform for research in systems biologyBioinformatics, 2005
- Biochemical network models simplified by balanced truncationThe FEBS Journal, 2005
- Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptorsNature Biotechnology, 2002