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首页> 外文期刊>BMC Bioinformatics >Steady state analysis of Boolean molecular network models via model reduction and computational algebra
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Steady state analysis of Boolean molecular network models via model reduction and computational algebra

机译:通过模型归约和计算代数对布尔分子网络模型进行稳态分析

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Background A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. Results This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. Conclusions The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem.
机译:背景技术分子网络数学模型分析中的关键问题是确定其稳态。本文针对布尔网络模型解决了这个问题,布尔网络模型是缺少详细动力学信息的网络的一种越来越流行的建模范例。对于小型模型,可以通过穷举所有状态转换来解决该问题。但是对于较大的模型,这是不可行的,因为相空间的大小会随网络的尺寸呈指数增长。已发布模型的尺寸正在增长到100多个,因此有效的稳态确定方法至关重要。对于大型网络,已经提出了几种方法,其中一些是启发式的。尽管这些方法相对于穷举枚举代表了可伸缩性的实质性改进,但大型网络的问题通常仍未解决。结果本文提出了一种算法,该算法包括两个主要部分。首先是网络布线图的图形理论简化,同时保留了有关稳态的所有信息。第二部分将确定布尔网络的所有稳态作为解决在具有两个元素的有限数系统上找到多项式方程组的所有解的问题。可以使用现有的计算机代数软件解决此问题。该算法与几种用于确定稳态的现有算法相比具有优势。一个优点是它不是启发式或依赖于采样,而是算法上确定布尔网络的所有稳态。可根据相应作者的要求获得该算法的代码以及基准网络的测试套件。结论本文提出的算法能够可靠地确定具有多达1000个节点的稀疏布尔网络的所有稳态。该算法可有效分析几乎所有已发布的模型,即使是中等连通性的模型。具有高平均连接性的大型布尔网络的问题仍然是一个未解决的问题。

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