@inbook{45b3e119b1424b79862fee2d4344d7df,
title = "The advantage of global fitting of data involving complex linked reactions",
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.",
keywords = "Monte Carlo analysis, Nonlinear least squares, Two-state allosteric model",
author = "Petr Herman and Lee, {J. Ching}",
year = "2012",
doi = "10.1007/978-1-61779-334-9_22",
language = "English (US)",
isbn = "9781617793332",
series = "Methods in Molecular Biology",
pages = "399--421",
editor = "A.W. Fenton",
booktitle = "Allostery",
}