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The statistical analysis of enzyme kinetic reactions usually involves modelsof the response functions which are well defined on the basis ofMichaelis-Menten type equations. The error structure however is often withoutgood reason assumed as additive Gaussian noise. This simple assumption may leadto undesired properties of the analysis, particularly when simulations areinvolved and consequently negative simulated reaction rates may occur. In thisstudy we investigate the effect of assuming multiplicative lognormal errorsinstead. While there is typically little impact on the estimates, theexperimental designs and their efficiencies are decisively affected,particularly when it comes to model discrimination problems.

Impact of the error structure on the design and analysis of enzyme kinetic models