Format

Send to

Choose Destination
See comment in PubMed Commons below
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 May;71(5 Pt 2):056103. Epub 2005 May 6.

Subgraph centrality in complex networks.

Author information

  • 1Complex Systems Research Group, X-Rays Unit, RIAIDT, Edificio CACTUS, University of Santiago de Compostela, 15706 Santiago de Compostela, Spain. estrada66@yahoo.com

Abstract

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 [C(S)(i)] 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 C(S)(i) 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 C(S)(i) (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.

Comment in

PMID:
16089598
DOI:
10.1103/PhysRevE.71.056103
[PubMed]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Loading ...
    Support Center