Estrada Ernesto, Higham Desmond J, Hatano Naomichi
Institute of Complexity Science, Department of Physics and Department of Mathematics, University of Strathclyde, Glasgow G1 1XH, United Kingdom.
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Aug;78(2 Pt 2):026102. doi: 10.1103/PhysRevE.78.026102. Epub 2008 Aug 8.
We here present a method of clearly identifying multipartite subgraphs in a network. The method is based on a recently introduced concept of the communicability, which very clearly identifies communities in a complex network. We here show that, while the communicability at a positive temperature is useful in identifying communities, the communicability at a negative temperature is useful in identifying multipartite subgraphs; the latter quantity between two nodes is positive when the two nodes belong to the same subgraph and is negative when they do not. The method is able to discover "almost" multipartite structures, where intercommunity connections vastly outweigh intracommunity connections. We illustrate the relevance of this work to real-life food web and protein-protein interaction networks.
我们在此提出一种在网络中清晰识别多部分子图的方法。该方法基于最近引入的可通信性概念,它能非常清晰地识别复杂网络中的群落。我们在此表明,虽然正温度下的可通信性有助于识别群落,但负温度下的可通信性有助于识别多部分子图;当两个节点属于同一子图时,这两个节点之间的后一个量为正,当它们不属于同一子图时为负。该方法能够发现“几乎”多部分结构,其中群落间连接远多于群落内连接。我们阐述了这项工作与现实生活中的食物网和蛋白质 - 蛋白质相互作用网络的相关性。