Valverde Sergi, Solé Ricard V
ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr. Aiguader 80, 08003 Barcelona, Spain.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Aug;72(2 Pt 2):026107. doi: 10.1103/PhysRevE.72.026107. Epub 2005 Aug 8.
Complex networks in both nature and technology have been shown to display characteristic, small subgraphs (so-called motifs) which appear to be related to their underlying functionality. All these networks share a common trait: they manipulate information at different scales in order to perform some kind of computation. Here we analyze a large set of software class diagrams and show that several highly frequent network motifs appear to be a consequence of network heterogeneity and size, thus suggesting a somewhat less relevant role of functionality. However, by using a simple model of network growth by duplication and rewiring, it is shown the rules of graph evolution seem to be largely responsible for the observed motif distribution.
自然界和技术领域中的复杂网络已被证明会展现出具有特征性的小子图（即所谓的模体），这些模体似乎与其潜在功能相关。所有这些网络都有一个共同特征：它们在不同尺度上处理信息以便执行某种计算。在此，我们分析了大量软件类图，并表明一些高频网络模体似乎是网络异质性和规模的结果，从而暗示功能的作用相对较小。然而，通过使用一个由复制和重新布线构成的简单网络增长模型，结果表明图演化规则似乎在很大程度上决定了观察到的模体分布。
