Serrano M Angeles, De Los Rios Paolo
IFISC (CSIC-UIB), Instituto de Física Interdisciplinar y Sistemas Complejos, Campus Universitat Illes Balears, Palma de Mallorca, Spain.
PLoS One. 2008;3(11):e3654. doi: 10.1371/journal.pone.0003654. Epub 2008 Nov 5.
The large-scale structure of complex systems is intimately related to their functionality and evolution. In particular, global transport processes in flow networks rely on the presence of directed pathways from input to output nodes and edges, which organize in macroscopic connected components. However, the precise relation between such structures and functional or evolutionary aspects remains to be understood. Here, we investigate which are the constraints that the global structure of directed networks imposes on transport phenomena. We define quantitatively under minimal assumptions the structural efficiency of networks to determine how robust communication between the core and the peripheral components through interface edges could be. Furthermore, we assess that optimal topologies in terms of access to the core should look like "hairy balls" so to minimize bottleneck effects and the sensitivity to failures. We illustrate our investigation with the analysis of three real networks with very different purposes and shaped by very different dynamics and time-scales-the Internet customer-provider set of relationships, the nervous system of the worm Caenorhabditis elegans, and the metabolism of the bacterium Escherichia coli. Our findings prove that different global connectivity structures result in different levels of structural efficiency. In particular, biological networks seem to be close to the optimal layout.
复杂系统的大规模结构与其功能和演化密切相关。特别是,流网络中的全局传输过程依赖于从输入节点到输出节点以及边的有向路径的存在,这些路径在宏观连通组件中组织起来。然而,这种结构与功能或演化方面之间的确切关系仍有待理解。在这里,我们研究有向网络的全局结构对传输现象施加了哪些限制。我们在最小假设下定量定义网络的结构效率,以确定通过接口边在核心组件和外围组件之间进行稳健通信的程度。此外,我们评估就访问核心而言的最优拓扑结构应该看起来像“毛球”,以便最小化瓶颈效应和对故障的敏感性。我们通过分析三个具有非常不同目的、由非常不同的动力学和时间尺度塑造的真实网络——互联网客户 - 供应商关系集、秀丽隐杆线虫的神经系统以及大肠杆菌的代谢系统,来说明我们的研究。我们的发现证明,不同的全局连通性结构导致不同水平的结构效率。特别是,生物网络似乎接近最优布局。