Quantifying robustness of biochemical network models

Lan Ma, Pablo A. Iglesias

Research output: Contribution to journalArticle

100 Citations (Scopus)

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

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Biochemical Networks
Network Model
Value engineering
Theoretical Models
Robustness
Singular Values
Limit Cycle
Sensitivity analysis
Quantify
Oscillation
Mathematical models
Parameter Sensitivity
Bifurcation Analysis
Robust Stability
Sensitivity Analysis
Vary
Model
Mathematical Model
Engineering
Evaluate

ASJC Scopus subject areas

  • Medicine(all)
  • Structural Biology
  • Applied Mathematics

Cite this

Quantifying robustness of biochemical network models. / Ma, Lan; Iglesias, Pablo A.

In: BMC Bioinformatics, Vol. 3, 38, 13.12.2002.

Research output: Contribution to journalArticle

Ma, Lan ; Iglesias, Pablo A. / Quantifying robustness of biochemical network models. In: BMC Bioinformatics. 2002 ; Vol. 3.
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