Exploring the morphospace of communication efficiency in complex networks.
Exploring the morphospace of communication efficiency in complex networks.
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DOI：
10.1371/journal.pone.0058070
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Sporns O
中科院分区：
文献类型：
--
作者：
Goñi J;Avena-Koenigsberger A;Velez de Mendizabal N;van den Heuvel MP;Betzel RF;Sporns O
图论分析在表征复杂网络拓扑结构的全局特征方面发挥了关键作用，描述了蛋白质相互作用，食物网，社会关系和大脑连接等多种系统。系统元素如何相互通信不仅取决于网络的结构，而且还取决于系统的动态特性，这些动态特性受到可用于通信过程的知识和资源的量的约束。补充广泛使用的措施，捕获效率的假设下，通信优先遵循最短路径在网络中（“路由”），我们定义的分析措施，旨在表征网络通信时，信号流在一个随机游走过程（“扩散”）。路由和扩散效率的两个维度定义了复杂网络的形态空间，不同的网络拓扑结构以效率度量的不同组合为特征，因此占据了这个空间的不同区域。我们通过检查规范的网络模型，通过使用多目标优化策略发展网络，并通过调查现实世界的网络数据集，探索网络拓扑结构和效率措施的关系。在效率morphospace，网络拓扑结构的具体方面，差异有利于有效的通信路由和扩散过程中确定。绘制由规范的、进化的或真实的网络占据的形态空间区域，可以推断出连通性和动态性对通信效率的限制，以及塑造网络拓扑结构的潜在选择压力。
Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network (“routing”), we define analytic measures directed at characterizing network communication when signals flow in a random walk process (“diffusion”). The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.
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