Attractor analysis of asynchronous Boolean models of signal transduction networks
Attractor analysis of asynchronous Boolean models of signal transduction networks
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DOI：
10.1016/j.jtbi.2010.07.022
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发表时间：
2010-10-21
影响因子：
2
通讯作者：
Albert, Reka
中科院分区：
文献类型：
--
作者：
Saadatpour, Assieh;Albert, Istvan;Albert, Reka
以往对布尔网络动力学的研究，包括对状态空间吸引子和每个吸引子的吸引域的分析，主要集中在节点状态的同步更新上。虽然同步更新的简单性使其非常有吸引力，但它没有考虑到与不同类型的生物过程相关的各种时间尺度。人们已经提出了几种不同的异步更新方法来克服这一局限性，但还没有对同一系统在不同更新方法下的动态行为进行任何系统的比较。在这里，我们通过结合理论分析，如标量方程的解和马尔可夫链技术，以及数值模拟，对以前提出的植物信号转导网络的布尔模型的动态行为进行深入的比较研究，以填补这一空白。先前的证据表明，这个网络承认存在振荡，但这些振荡是否持续尚不清楚。我们使用同步和三种不同的异步更新方案对该系统进行了吸引子分析，其中包括未扰动(野生型)和扰动(节点扰动)系统。这一分析表明，虽然野生型系统存在一个与更新无关的不动点，但除非满足对某些过程的时间和系统初始状态的严格约束，否则任何振荡最终都会消失。有趣的是，在特定节点中断的情况下，所有模型都会导致扩展的吸引子。总体而言，我们的工作提供了一个路线图，说明布尔网络建模如何作为一种预测工具来揭示生物系统在各种内部和环境扰动下的动态模式。(C)2010爱思唯尔有限公司。保留所有权利。
Prior work on the dynamics of Boolean networks, including analysis of the state space attractors and the basin of attraction of each attractor, has mainly focused on synchronous update of the nodes' states. Although the simplicity of synchronous updating makes it very attractive, it fails to take into account the variety of time scales associated with different types of biological processes. Several different asynchronous update methods have been proposed to overcome this limitation, but there have not been any systematic comparisons of the dynamic behaviors displayed by the same system under different update methods. Here we fill this gap by combining theoretical analysis such as solution of scalar equations and Markov chain techniques, as well as numerical simulations to carry out a thorough comparative study on the dynamic behavior of a previously proposed Boolean model of a signal transduction network in plants. Prior evidence suggests that this network admits oscillations, but it is not known whether these oscillations are sustained. We perform an attractor analysis of this system using synchronous and three different asynchronous updating schemes both in the case of the unperturbed (wild-type) and perturbed (node-disrupted) systems. This analysis reveals that while the wild-type system possesses an update-independent fixed point, any oscillations eventually disappear unless strict constraints regarding the timing of certain processes and the initial state of the system are satisfied. Interestingly, in the case of disruption of a particular node all models lead to an extended attractor. Overall, our work provides a roadmap on how Boolean network modeling can be used as a predictive tool to uncover the dynamic patterns of a biological system under various internal and environmental perturbations. (c) 2010 Elsevier Ltd. All rights reserved.