Exploiting the bootstrap method for quantifying parameter confidence intervals in dynamical systems

Metab Eng. 2006 Sep;8(5):447-55. doi: 10.1016/j.ymben.2006.04.003. Epub 2006 May 6.


A quantitative description of dynamical systems requires the estimation of uncertain kinetic parameters and an analysis of their precision. A method frequently used to describe the confidence intervals of estimated parameters is based on the Fisher-Information-Matrix. The application of this traditional method has two important shortcomings: (i) it gives only lower bounds for the variance of a parameter if the solution of the underlying model equations is non-linear in parameters. (ii) The resulting confidence interval is symmetric with respect to the estimated parameter. Here, we show that by applying the bootstrap method a better approximation of (possibly) asymmetric confidence intervals for parameters could be obtained. In contrast to previous applications devoted to non-parametric problems, a dynamical model describing a bio-chemical network is used to evaluate the method.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Cell Physiological Phenomena*
  • Computer Simulation
  • Models, Biological*
  • Proteome / metabolism*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Signal Transduction / physiology*


  • Proteome