Verification of Biochemical Processes Using Stochastic Hybrid Systems

D. Riley, X. Koutsoukos, K. Riley
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引用次数: 8

Abstract

Modeling and analysis of biochemical systems are critical problems because they can provide new insights into systems which can not be easily tested with real experiments. One such biochemical process is the formation of sugar cataracts in the lens of an eye. Analyzing the sugar cataract development process is a challenging problem due to the highly-coupled chemical reactions that are involved. In this paper we model sugar cataract development as a stochastic hybrid system. Based on this model, we present a probabilistic verification method for computing the probability of sugar cataract formation for different chemical concentrations. Our analysis can potentially provide useful insights into the complicated dynamics of the process and assist in focusing experiments on specific regions of concentrations. The verification method employs dynamic programming based on a discretization of the state space and therefore suffers from the curse of dimensionality. To verify the sugar cataract development process we have developed a parallel dynamic programming implementation that can handle large systems. Although scalability is a limiting factor, this work demonstrates that the technique is feasible for realistic biochemical systems.
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用随机混合系统验证生化过程
生化系统的建模和分析是关键问题,因为它们可以为系统提供新的见解,而这些系统不容易通过实际实验进行测试。其中一个生物化学过程就是眼睛晶状体中糖性白内障的形成。由于涉及高耦合的化学反应,分析糖白内障的形成过程是一个具有挑战性的问题。本文将糖性白内障的发育建模为一个随机杂交系统。在此模型的基础上,提出了一种计算不同化学浓度下糖性白内障形成概率的概率验证方法。我们的分析可能会对这一过程的复杂动力学提供有用的见解,并有助于将实验集中在特定的浓度区域。验证方法采用基于状态空间离散化的动态规划方法,因此存在维数诅咒的问题。为了验证糖白内障的发展过程,我们开发了一个可以处理大型系统的并行动态规划实现。虽然可扩展性是一个限制因素,但这项工作表明,该技术对于现实的生化系统是可行的。
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