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A compositional framework for Boolean networks

机译:布尔网络的组成框架

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摘要

Boolean networks are a widely used qualitative approach for modelling and analysing biological systems. However, their application is restricted by the well-known state space explosion problem which means that modelling large-scale, realistic biological systems is challenging. In this paper we set out to facilitate the construction and analysis of large scale biological models by developing a formal framework for the composition of Boolean networks. The compositional approach we present is based on merging entities between Boolean networks using a binary Boolean operator and we formalise the preservation of behaviour under composition using a notion of compatibility. We investigate characterising compatibility in terms of the composed models by developing a trace alignment property. In particular, we use a formalisation of the interference that can occur in a composed model to define an extended trace alignment property that we show completely characterises compatibility.
机译:布尔网络是一种广泛使用的模拟和分析生物系统的定性方法。 然而,他们的应用受到着名的状态空间爆炸问题的限制,这意味着建模大规模,现实的生物系统是挑战性的。 在本文中,我们首先通过开发布尔网络组成的正式框架来促进大规模生物模型的建设和分析。 我们所呈现的组成方法是基于使用二进制布尔运算符在布尔网络之间的合并实体,并且我们使用兼容性的概念正式确定组合下的行为保存。 我们通过开发跟踪对准属性来调查表征组合模型的兼容性。 特别是,我们使用可以在组合模型中发生的干扰的正式化来定义我们显示完全表征兼容性的扩展跟踪对齐属性。

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