Abstract
One of the most ambitious and challenging goals of systems biology is the identification oftargets for reshaping biological systems based on quantitative predictions with the aid of mathematicalmodels. Whereas the potential and promise of biological systems modelling is substantial, severalobstacles are still encountered when addressing the issue of predictive design based on dynamic models.This is particularly because of the well known difficulties in assessing enzyme kinetics under in vivo conditions as a prerequisite for a sound quantitative analysis ofthe network via dynamic modelling. The article will describe developments and applications of toolsaimed at achieving sustained improvements within this important field. Our experience in using metabolitedata for reconstruction of dynamic models led to a dual approach. At the core of the modular conceptis the decomposition of the networks into manageable subunits. Furthermore, a new top down approachis presented for estimating kinetic parameters for the individual reactions in whole cell metabolicnetworks from time series data.
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Reuss, M., Aguilera-Vázquez, L., Mauch, K. (2007). Reconstruction of dynamic network models from metabolite measurements. In: Nielsen, J., Jewett, M.C. (eds) Metabolomics. Topics in Current Genetics, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/4735_2007_0219
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DOI: https://doi.org/10.1007/4735_2007_0219
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