The advantage of global fitting of data involving complex linked reactions

Petr Herman, James Lee

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Scopus citations

Abstract

In this chapter, we demonstrate the advantage of the simultaneous multicurve nonlinear least-squares analysis over that of the conventional single-curve analysis. Fitting results are subjected to thorough Monte Carlo analysis for rigorous assessment of confidence intervals and parameter correlations. The comparison is performed on a practical example of simulated steady-state reaction kinetics complemented with isothermal calorimetry (ITC) data resembling allosteric behavior of rabbit muscle pyruvate kinase (RMPK). Global analysis improves accuracy and confidence limits of model parameters. Cross-correlation between parameters is also reduced with accompanying enhancement of the model-testing power. This becomes especially important for validation of models with "difficult" highly cross-correlated parameters. We show how proper experimental design and critical evaluation of data can improve the chance of differentiating models.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
Pages399-421
Number of pages23
Volume796
DOIs
StatePublished - 2012

Publication series

NameMethods in Molecular Biology
Volume796
ISSN (Print)10643745

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Keywords

  • Monte Carlo analysis
  • Nonlinear least squares
  • Two-state allosteric model

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

Cite this

Herman, P., & Lee, J. (2012). The advantage of global fitting of data involving complex linked reactions. In Methods in Molecular Biology (Vol. 796, pp. 399-421). (Methods in Molecular Biology; Vol. 796). https://doi.org/10.1007/978-1-61779-334-9_22