Quantifying robustness of biochemical network models

Lan Ma, Pablo A. Iglesias

Research output: Contribution to journalArticle

102 Scopus citations

Abstract

Background: Robustness of mathematical models of biochemical networks is important for validation purposes and can be used as a means of selecting between different competing models. Tools for quantifying parametric robustness are needed. Results: Two techniques for describing quantitatively the robustness of an oscillatory model were presented and contrasted. Single-parameter bifurcation analysis was used to evaluate the stability robustness of the limit cycle oscillation as well as the frequency and amplitude of oscillations. A tool from control engineering - the structural singular value (SSV) - was used to quantify robust stability of the limit cycle. Using SSV analysis, we find very poor robustness when the model's parameters are allowed to vary. Conclusion: The results show the usefulness of incorporating SSV analysis to single parameter sensitivity analysis to quantify robustness.

Original languageEnglish (US)
Article number38
JournalBMC Bioinformatics
Volume3
DOIs
StatePublished - Dec 13 2002

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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