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Distinguishing enzymes using metabolome data for the hybrid dynamic/static method

机译:混合动态/静态方法使用代谢组学数据区分酶

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摘要

BackgroundIn the process of constructing a dynamic model of a metabolic pathway, a large number of parameters such as kinetic constants and initial metabolite concentrations are required. However, in many cases, experimental determination of these parameters is time-consuming. Therefore, for large-scale modelling, it is essential to develop a method that requires few experimental parameters. The hybrid dynamic/static (HDS) method is a combination of the conventional kinetic representation and metabolic flux analysis (MFA). Since no kinetic information is required in the static module, which consists of MFA, the HDS method may dramatically reduce the number of required parameters. However, no adequate method for developing a hybrid model from experimental data has been proposed.
机译:背景技术在构建代谢途径的动力学模型的过程中,需要大量参数,例如动力学常数和初始代谢物浓度。但是,在许多情况下,这些参数的实验确定很耗时。因此,对于大规模建模,开发一种几乎不需要实验参数的方法至关重要。动态/静态混合(HDS)方法是常规动力学表示和代谢通量分析(MFA)的组合。由于在包含MFA的静态模块中不需要动力学信息,因此HDS方法可能会大大减少所需参数的数量。但是,尚未提出从实验数据开发混合模型的适当方法。

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