Subgraph Centrality in Complex Networks

Details Subgraph Centrality in Complex Networks Subgraph Centrality in Complex Networks

2005-04-27

arxiv.org/abs/cond-mat/0504730v1

Physical Review E 71, 056103 (2005)

Physics

Condensed Matter

Statistical Mechanics

29 pages, 4 figures, 2 tables

Scientific paper

10.1103/PhysRevE.71.056103

We introduce a new centrality measure that characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than larger ones, which makes this measure appropriate for characterizing network motifs. We show that the subgraph centrality (SC) can be obtained mathematically from the spectra of the adjacency matrix of the network. This measure is better able to discriminate the nodes of a network than alternate measures such as degree, closeness, betweenness and eigenvector centralities. We study eight real-world networks for which SC displays useful and desirable properties, such as clear ranking of nodes and scale-free characteristics. Compared with the number of links per node, the ranking introduced by SC (for the nodes in the protein interaction network of S. cereviciae) is more highly correlated with the lethality of individual proteins removed from the proteome.

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