基于改进Hoare逻辑的基因网络混合模型约束识别

Time Pub Date : 2017-10-16 DOI:10.4230/LIPIcs.TIME.2017.5
Jonathan Behaegel, J. Comet, M. Folschette
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引用次数: 5

摘要

我们提出了一种新的混合Hoare逻辑,专门用于一类线性混合自动机,非常适合于模拟基因调控网络。这些自动机依赖于托马斯的离散框架,其中定性参数被称为速度的连续参数所取代。这些参数的识别仍然是建模过程的关键点之一,特别是因为建模框架是基于连续时间的,所以识别这些参数是困难的。我们引入Hoare三元组来处理生物痕迹和前置/后置条件。观察到的时间生物痕迹对经典霍尔逻辑起着命令式程序的作用,我们的混合霍尔逻辑,由推理规则定义,被证明是健全的。此外,我们提出了一个最弱前提演算(a la Dijkstra),它导致了动态参数的约束。最后,我们用一个简化的生物钟模型来说明我们的“约束生成器”,该模型描述了哺乳动物细胞在24小时内的节律性。
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Constraint Identification Using Modified Hoare Logic on Hybrid Models of Gene Networks
We present a new hybrid Hoare logic dedicated for a class of linear hybrid automata well suited to model gene regulatory networks. These automata rely on Thomas' discrete framework in which qualitative parameters have been replaced by continuous parameters called celerities. The identification of these parameters remains one of the keypoints of the modelling process, and is difficult especially because the modelling framework is based on a continuous time. We introduce Hoare triples which handle biological traces and pre/post-conditions. Observed chronometrical biological traces play the role of an imperative program for classical Hoare logic and our hybrid Hoare logic, defined by inference rules, is proved to be sound. Furthermore, we present a weakest precondition calculus (a la Dijkstra) which leads to constraints on dynamical parameters. Finally, we illustrate our " constraints generator " with a simplified circadian clock model describing the rhythmicity of cells in mammals on a 24-hour period.
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