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首页> 外文期刊>BMC Systems Biology >A multiscale approximation in a heat shock response model of E. coli
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A multiscale approximation in a heat shock response model of E. coli

机译:大肠杆菌热休克反应模型的多尺度近似

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Background A heat shock response model of Escherichia coli developed by Srivastava, Peterson, and Bentley (2001) has multiscale nature due to its species numbers and reaction rate constants varying over wide ranges. Applying the method of separation of time-scales and model reduction for stochastic reaction networks extended by Kang and Kurtz (2012), we approximate the chemical network in the heat shock response model. Results Scaling the species numbers and the rate constants by powers of the scaling parameter, we embed the model into a one-parameter family of models, each of which is a continuous-time Markov chain. Choosing an appropriate set of scaling exponents for the species numbers and for the rate constants satisfying balance conditions, the behavior of the full network in the time scales of interest is approximated by limiting models in three time scales. Due to the subset of species whose numbers are either approximated as constants or are averaged in terms of other species numbers, the limiting models are located on lower dimensional spaces than the full model and have a simpler structure than the full model does. Conclusions The goal of this paper is to illustrate how to apply the multiscale approximation method to the biological model with significant complexity. We applied the method to the heat shock response model involving 9 species and 18 reactions and derived simplified models in three time scales which capture the dynamics of the full model. Convergence of the scaled species numbers to their limit is obtained and errors between the scaled species numbers and their limit are estimated using the central limit theorem.
机译:背景技术Srivastava,Peterson和Bentley(2001)开发的大肠杆菌的热激响应模型由于其物种数量和反应速率常数在很宽的范围内变化而具有多尺度的性质。将时间尺度的分离和模型还原的方法应用于由Kang和Kurtz(2012)扩展的随机反应网络,我们在热激响应模型中近似化学网络。结果通过缩放参数的幂对物种数量和速率常数进行缩放,我们将模型嵌入到一个单参数模型家族中,每个模型都是连续时间马尔可夫链。为物种数量和满足平衡条件的速率常数选择一组合适的缩放指数,可以通过限制三个时间尺度的模型来近似整个网络在感兴趣的时间尺度上的行为。由于物种的子集的数量近似为常数或根据其他物种数量进行平均,因此限制模型位于比完整模型低的维空间上,并且结构比完整模型更简单。结论本文的目的是说明如何将多尺度逼近方法应用于具有显着复杂性的生物学模型。我们将该方法应用于涉及9个物种和18个反应的热激响应模型,并在三个时间尺度上导出了简化的模型,这些模型捕获了完整模型的动力学。获得缩放物种数到其极限的收敛性,并使用中心极限定理估计缩放物种数与其极限之间的误差。

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