A natural class of robust networks
A natural class of robust networks
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DOI：
10.1073/pnas.1536783100
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发表时间：
2003-07-22
影响因子：
11.1
通讯作者：
Cluzel, P
中科院分区：
文献类型：
--
作者：
Aldana, M;Cluzel, P
随着生物学研究从分子描述转向系统分析，我们需要确定大型细胞内网络的设计原则。特别是，在不知道分子细节的情况下，我们想要确定细胞如何可靠地执行基本的细胞内任务。最近对信号通路和调控转录网络的分析揭示了一个共同的网络结构，称为无标度拓扑。虽然这类网络的结构性质已经得到了深入的研究，但它们的动力学性质在很大程度上还没有被探索。我们提出了一个用于动力学系统研究的原型，以预测细胞内网络对其内部参数变化的功能稳健性。我们证明了这些复杂网络的动态稳健性是其无标度拓扑的直接结果。相比之下，具有同质随机拓扑的网络需要微调其内部参数以维持稳定的动态活动。考虑到自然界中无处不在的无标度网络，我们假设这种拓扑结构不仅是优先依附等聚集过程的结果，也可能是进化选择过程的结果。
As biological studies shift from molecular description to system analysis we need to identify the design principles of large intracellular networks. In particular, without knowing the molecular details, we want to determine how cells reliably perform essential intracellular tasks. Recent analyses of signaling pathways and regulatory transcription networks have revealed a common network architecture, termed scale-free topology. Although the structural properties of such networks have been thoroughly studied, their dynamical properties remain largely unexplored. We present a prototype for the study of dynamical systems to predict the functional robustness of intracellular networks against variations of their internal parameters. We demonstrate that the dynamical robustness of these complex networks is a direct consequence of their scale-free topology. By contrast, networks with homogeneous random topologies require fine-tuning of their internal parameters to sustain stable dynamical activity. Considering the ubiquity of scale-free networks in nature, we hypothesize that this topology is not only the result of aggregation processes such as preferential attachment; it may also be the result of evolutionary selective processes.