Reconstructing metabolic networks using interval analysis
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.