Metabolomics pp 97-127 | Cite as

Reconstruction of dynamic network models from metabolite measurements

  • Matthias Reuss
  • Luciano Aguilera-Vázquez
  • Klaus Mauch
Part of the Topics in Current Genetics book series (TCG, volume 18)


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.


Metabolic Network Intracellular Metabolite Metabolic Flux Analysis Metabolite Measurement Dynamic Network Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Matthias Reuss
    • 1
  • Luciano Aguilera-Vázquez
    • 2
  • Klaus Mauch
    • 3
  1. 1.Institute of Biochemical Engineering and Centre of Systems BiologyUniversity StuttgartStuttgartGermany
  2. BiotecnologíaUniversidad Politécnica de PachucaMunicipio de Zenpoala, HgoMexico
  3. 3.Insilico Biotechnology AGStuttgartGermany

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