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A Graph-Theoretic Approach to Design of Probabilistic Boolean Networks

机译:图论方法设计概率布尔网络

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In this paper, a graph-theoretic design method for a probabilistic Boolean network (PBN) is proposed. A PBN is well known as a mathematical model of complex network systems such as gene regulatory networks. In Boolean networks, interactions between binary states are modeled by Boolean functions. In PBNs, Boolean functions are switched probabilistically. In this paper, after a polynomial representation of a PBN is briefly explained, a simplified representation is proposed. Here, the steady value of the expected value of the state is focused, and is characterized by a minimum feedback vertex set of an interaction graph expressing interactions between states. Using this representation, input selection and stabilization are discussed. The proposed method is demonstrated by a biological example.
机译:本文提出了一种概率布尔网络(PBN)的图论设计方法。 PBN是众所周知的复杂网络系统(例如基因调控网络)的数学模型。在布尔网络中,二进制状态之间的交互作用是通过布尔函数建模的。在PBN中,布尔函数是概率切换的。在本文中,简要解释了PBN的多项式表示之后,提出了一种简化表示。在此,状态的期望值的稳定值受到关注,并且其特征在于表示状态之间的相互作用的相互作用图的最小反馈顶点集。使用这种表示,讨论了输入选择和稳定化。通过生物学实例证明了所提出的方法。

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