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A Switched Systems Approach for the Analysis and Control of Mode Transitions in Biological Networks

机译:一种切换系统方法,用于分析和控制生物网络中模式转换的方法

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This work present a methodology for the analysis and control of mode transitions in biological networks. The proposed approach is predicated upon the notion of orchestrating switching between the domains of attraction of the steady-states of the constituent modes. Initially, the overall network is modeled as a switched nonlinear system that consists of multiple modes, each governed by a set of continuous-time differential equations. The transitions between the continuous modes are triggered by discrete events (changes in model parameters that correspond to alterations in physiological conditions). Then, following the characterization of the steady-state behavior of each mode, Lyapunov techniques are used to characterize the domains of attraction of the steady-states. Finally, by analyzing how the domains of attraction of the various modes overlap with one other, a switching rule is derived to determine when, and if, a given mode transition at a given time results in the desired steady-state behavior. The proposed approach has implications both for understanding the outcome of naturally-occurring mode transitions and for the ability to manipulate network behavior by enforcing mode transitions. The proposed approach is demonstrated using a model of a biological network that arises in the bacteriophage λ-switch system.
机译:这项工作提出了一种方法,用于分析和生物网络模式转换的控制。所提出的方法是在统筹的构成模式的稳定状态的吸引域之间切换的概念预测。最初,整体网络建模为一个由多个模式,每个由一组连续时间微分方程支配的非线性切换系统。连续模式之间的转换由离散的事件触发(在模型参数的变化对应于在生理条件的改变)。然后,将各模式的稳态行为的表征以下,李雅普诺夫技术被用来表征稳定状态的吸引域。最后,通过分析如何各种模式的吸引结构域与一个重叠,切换规则导出,以确定何时,并且如果在给定的时间的结果的给定的模式转变所需的稳态行为。所提出的方法既具有理解自然发生模式转换的成果和通过强制执行模式转换到操作网络行为的能力的影响。所提出的方法是使用中出现的噬菌体λ-开关系统的生物网络的模型证实。

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