Reconstructing metabolic networks using interval analysis

Warwick Tucker, Uppsala University, Uppsala

Recently, modeling and simulation of metabolic networks has attracted a great deal of attention. The majority of such models are given in terms of coupled ordinary differential equations, whose parameters correspond to various kinetic rates of the underlying chemical reactions. One of the main challenges is to reconstruct approximate values of these parameters, given measured time traces of the involved reactants. Efficient reconstruction procedures enable in silico experiments aimed at investigating the dynamical behavior of metabolic networks for a wide range of parameters. We propose a novel method for parameter reconstruction, based on interval analysis, and illustrate the strength of our method by employing it to reconstruct metabolic networks using S-systems.


Vincent Moulton
© 2005, CBL
Computational Biology Laboratory,
School of Computing Sciences,
University of East Anglia,
Norwich, NR4 7TJ, UK.