Schmidt Henning, Madsen Mads F, Danø Sune, Cedersund Gunnar
Systems Biology and Bioinformatics Group, University of Rostock, Rostock, Germany.
Bioinformatics. 2008 Mar 15;24(6):848-54. doi: 10.1093/bioinformatics/btn035. Epub 2008 Feb 10.
The current trend in dynamical modelling of biochemical systems is to construct more and more mechanistically detailed and thus complex models. The complexity is reflected in the number of dynamic state variables and parameters, as well as in the complexity of the kinetic rate expressions. However, a greater level of complexity, or level of detail, does not necessarily imply better models, or a better understanding of the underlying processes. Data often does not contain enough information to discriminate between different model hypotheses, and such overparameterization makes it hard to establish the validity of the various parts of the model. Consequently, there is an increasing demand for model reduction methods.
We present a new reduction method that reduces complex rational rate expressions, such as those often used to describe enzymatic reactions. The method is a novel term-based identifiability analysis, which is easy to use and allows for user-specified reductions of individual rate expressions in complete models. The method is one of the first methods to meet the classical engineering objective of improved parameter identifiability without losing the systems biology demand of preserved biochemical interpretation.
The method has been implemented in the Systems Biology Toolbox 2 for MATLAB, which is freely available from http://www.sbtoolbox2.org. The Supplementary Material contains scripts that show how to use it by applying the method to the example models, discussed in this article.
当前生化系统动力学建模的趋势是构建越来越多机制详细因而也越来越复杂的模型。这种复杂性体现在动态状态变量和参数的数量上，以及动力学速率表达式的复杂性上。然而，更高程度的复杂性或细节程度并不一定意味着更好的模型，或者对潜在过程有更好的理解。数据通常不包含足够的信息来区分不同的模型假设，这种过度参数化使得难以确定模型各个部分的有效性。因此，对模型简化方法的需求日益增加。
我们提出了一种新的简化方法，该方法可简化复杂的有理速率表达式，例如常用于描述酶促反应的那些表达式。该方法是一种新颖的基于项的可识别性分析，易于使用，并允许用户指定对完整模型中各个速率表达式进行简化。该方法是首批满足经典工程目标（即提高参数可识别性）同时又不丧失系统生物学对保留生化解释的要求的方法之一。
该方法已在用于MATLAB的系统生物学工具箱2中实现，可从http://www.sbtoolbox2.org免费获取。补充材料包含脚本，展示了如何通过将该方法应用于本文讨论的示例模型来使用它。
