计算机程序
多样性(控制论)
估计理论
计算机科学
曲线拟合
实验数据
估计
代数数
算法
应用数学
数学
数据挖掘
统计
人工智能
机器学习
工程类
数学分析
操作系统
系统工程
作者
Michael Zavrel,Karl Kochanowski,Antje C. Spieß
标识
DOI:10.1002/elsc.200900083
摘要
Abstract For the analysis of enzyme kinetics, a variety of programs exists. These programs apply either algebraic or dynamic parameter estimation, requiring different approaches for data fitting. The choice of approach and computer program is usually subjective, and it is generally assumed that this choice has no influence on the obtained parameter estimates. However, this assumption has not yet been verified comprehensively. Therefore, in this study, five computer programs for progress curve analysis were compared with respect to accuracy and minimum data amount required to obtain accurate parameter estimates. While two of these five computer programs (MS‐Excel, Origin) use algebraic parameter estimation, three computer programs (Encora, ModelMaker, gPROMS) are able to perform dynamic parameter estimation. For this comparison, the industrially important enzyme penicillin amidase (EC 3.5.1.11) was studied, and both experimental and in silico data were used. It was shown that significant differences in the estimated parameter values arise by using different computer programs, especially if the number of data points is low. Therefore, deviations between parameter values reported in the literature could simply be caused by the use of different computer programs.
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