Mannervik B, Jakobson I, Warholm M
Biochem J. 1986 May 1;235(3):797-804. doi: 10.1042/bj2350797.
Optimal design of experiments as well as proper analysis of data are dependent on knowledge of the experimental error. A detailed analysis of the error structure of kinetic data obtained with acetylcholinesterase showed conclusively that the classical assumptions of constant absolute or constant relative error are inadequate for the dependent variable (velocity). The best mathematical models for the experimental error involved the substrate and inhibitor concentrations and reflected the rate law for the initial velocity. Data obtained with other enzymes displayed similar relationships between experimental error and the independent variables. The new empirical error functions were shown superior to previously used models when utilized in weighted non-linear-regression analysis of kinetic data. The results suggest that, in the spectrophotometric assays used in the present study, the observed experimental variance is primarily due to errors in determination of the concentrations of substrate and inhibitor and not to error in measuring the velocity.
实验的优化设计以及数据的恰当分析取决于对实验误差的了解。对用乙酰胆碱酯酶获得的动力学数据的误差结构进行详细分析，最终表明，关于恒定绝对误差或恒定相对误差的经典假设对于因变量（速度）而言是不充分的。实验误差的最佳数学模型涉及底物和抑制剂浓度，并反映了初始速度的速率定律。用其他酶获得的数据显示出实验误差与自变量之间存在类似的关系。当用于动力学数据的加权非线性回归分析时，新的经验误差函数比以前使用的模型更优越。结果表明，在本研究中使用的分光光度测定法中，观察到的实验方差主要是由于底物和抑制剂浓度测定中的误差，而不是速度测量中的误差。
