Danø Sune, Madsen Mads F, Schmidt Henning, Cedersund Gunnar
Department of Medical Biochemistry and Genetics, University of Copenhagen, Denmark.
FEBS J. 2006 Nov;273(21):4862-77. doi: 10.1111/j.1742-4658.2006.05485.x. Epub 2006 Sep 28.
The complexity of full-scale metabolic models is a major obstacle for their effective use in computational systems biology. The aim of model reduction is to circumvent this problem by eliminating parts of a model that are unimportant for the properties of interest. The choice of reduction method is influenced both by the type of model complexity and by the objective of the reduction; therefore, no single method is superior in all cases. In this study we present a comparative study of two different methods applied to a 20D model of yeast glycolytic oscillations. Our objective is to obtain biochemically meaningful reduced models, which reproduce the dynamic properties of the 20D model. The first method uses lumping and subsequent constrained parameter optimization. The second method is a novel approach that eliminates variables not essential for the dynamics. The applications of the two methods result in models of eight (lumping), six (elimination) and three (lumping followed by elimination) dimensions. All models have similar dynamic properties and pin-point the same interactions as being crucial for generation of the oscillations. The advantage of the novel method is that it is algorithmic, and does not require input in the form of biochemical knowledge. The lumping approach, however, is better at preserving biochemical properties, as we show through extensive analyses of the models.
全尺度代谢模型的复杂性是其在计算系统生物学中有效应用的主要障碍。模型简化的目的是通过去除对感兴趣的特性不重要的模型部分来规避这一问题。简化方法的选择既受模型复杂性类型的影响，也受简化目标的影响；因此，没有一种方法在所有情况下都是 superior 的。在本研究中，我们对应用于酵母糖酵解振荡的 20 维模型的两种不同方法进行了比较研究。我们的目标是获得具有生化意义的简化模型，这些模型能够重现 20 维模型的动态特性。第一种方法使用集总法和随后的约束参数优化。第二种方法是一种新颖的方法，它消除了对动力学不重要的变量。这两种方法的应用产生了八维（集总法）、六维（消除法）和三维（先集总后消除法）的模型。所有模型都具有相似的动态特性，并指出相同的相互作用对振荡的产生至关重要。新方法的优点是它是算法性的，不需要生化知识形式的输入。然而，正如我们通过对模型的广泛分析所表明的那样，集总法在保留生化特性方面表现更好。
