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酶动力学中进展曲线的分析:微分法和积分法中的偏差与收敛集

Analysis of progress curves in enzyme kinetics: bias and convergent set in the differential and in the integral method.

作者信息

Markus M, Plesser T, Kohlmeier M

出版信息

J Biochem Biophys Methods. 1981 Feb;4(2):81-90. doi: 10.1016/0165-022x(81)90021-x.

Abstract

Two problems encountered in the analysis of progress curves are examined: 1. Systematic deviations due to errors in the initial solute concentrations make the least-squares method unsuitable. The improvements accomplished by the introduction of a proper weighting matrix are investigated. 2. Non-linear parameter optimization implies a dependence of the optimized parameters on their initial estimates, due to the existence of multiple minima. It is shown that the sensitivity of the optimized parameters on the initial estimates is reduced by fitting the slopes of the progress curves. A subsequent fit of the original progress curve data is recommended for refinement of the parameters.

摘要

研究了在分析进展曲线时遇到的两个问题

  1. 由于初始溶质浓度误差导致的系统偏差使得最小二乘法不适用。研究了通过引入适当的加权矩阵所实现的改进。2. 非线性参数优化意味着由于存在多个最小值,优化参数依赖于它们的初始估计值。结果表明,通过拟合进展曲线的斜率可以降低优化参数对初始估计值的敏感性。建议随后对原始进展曲线数据进行拟合以优化参数。

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