Glophyt: a User-Friendly, General-Purpose Program for Nonlinear and Multidimensional Curve Fitting via a Hybrid Stochastic and Deterministic Approach

Author(s): Georges Czaplicki, Serge Mazeres.

Model validation depends on the agreement between the predicted and experimental data. However, finding solutions to problems, described by equations with many parameters, where even their orders of magnitude are not known, is a difficult task. This makes curve fitting very difficult in case of multidimensional and nonlinear data. This article presents a graphical user interface-based program employing a hybrid stochastic and deterministic approach, which allows for easy and reliable determination of model parameters by minimizing the differences between measured data and those calculated on the basis of a mathematical expression. The program has been extensively used in several laboratories and has proven to be efficient in determining model parameters in many different fields, such as pharmacological studies of ligand?receptor binding, entomological studies of populations, bacterial growth, photosynthesis, toxicology, differential scanning calorimetry, isothermal titration calorimetry and nuclear magnetic resonance spectroscopy. It is an effective solution for researchers facing the problem of estimating model parameters from multidimensional and nonlinear data where the orders of magnitude of parameters are not known.

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