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Current methods for fitting integrated rate equations to enzyme progress curves treat each observation as if it were an independent measurement. When the data are obtained by taking several successive readings from each of a series of progress curves, the data will not be truly independent and will exhibit autocorrelation. Here we propose a simple pragmatic extension of integrated rate equations which takes account of first-order autocorrelations. The value of the method is assessed when applied to five sets of experimental data.

A single-parameter family of adjustments for fitting enzyme kinetic models to progress-curve data