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Analysis of a Model Reduction Method (D-QSSA) applied to a Class of Biochemical Networks ?

机译:模型减少方法(D-QSSA)应用于一类生物化学网络

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摘要

This paper is aimed to develop and test one novel and unexplored enhancement of the classical model reduction method applied to a class of biochemical networks. Both methods, being (i) the standard quasi-steady-state approximation (QSSA), and (ii) the so-called delayed-QSSA methods are extensively presented. Specially, the numerical issues related to the setting of constant delays are discussed. Finally, for one slightly modified version of an enzyme-substrate reaction network (Michaelis-Menten kinetics), the comparison of the full non-reduced system behavior with respective variants of reduced model is presented and future prospects are proposed.
机译:本文旨在开发和测试应用于一类生化网络的经典模型减少方法的一种新颖和未开发的增强。 这两种方法都是(i)标准的准稳态近似(QSSA)和(ii)被广泛地呈现所谓的延迟QSSA方法。 特别地,讨论了与恒定延迟设置相关的数值问题。 最后,对于酶 - 衬底反应网络(Michaelis-Menten动力学)的一种略微修饰的版本,提出了与减少模型的各种变体的全部非减少系统行为的比较,并提出了未来的前景。

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