title: Fitting of enzyme kinetic data without prior knowledge of weights.
abstract: A method is described for fitting equations to enzyme kinetic data that requires minimal assumptions about the error structure of the data. The dependence of the variances on the velocities is not assumed, but is deduced from internal evidence in the data. The effect of very bad observations ('outliers') is mitigated by decreasing the weight of observations that give large deviations from the fitted equation. The method works well in a wide range of circumstances when applied to the Michaelis-Menten equation, but it is not limited to this equation. It can be applied to most of the equations in common use for the analysis of steady-state enzyme kinetics. It has been implemented as a computer program that can fit a wide variety of equations with two, three or four parameters and two or three variables.
mesh_terms: D002384:Catalysis; D003201:Computers; D004798:Enzymes / Q000378:metabolism*; D007700:Kinetics; D008722:Methods; D013223:Statistics as Topic
chemical_list: D004798:Enzymes