Generalized walks-based centrality measures for complex biological networks

E. Estrada

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)

Abstract

A strategy for zooming in and out the topological environment of a node in a complex network is developed. This approach is applied here to generalize the subgraph centrality of nodes in complex networks. In this case the zooming in strategy is based on the use of some known matrix functions which allow focusing locally on the environment of a node. When a zooming out strategy is applied new matrix functions are introduced, which give a more global picture of the topological surrounds of a node. These indices permit a modulation of the scales at which the environment of a node influences its centrality. We apply them to the study of 10 protein-protein interaction (PPI) networks. We illustrate the similarities and differences between the generalized subgraph centrality indices as well as among them and some classical centrality measures. We show here that the use of centrality indices based on the zooming in strategy identifies a larger number of essential proteins in the yeast PPI network than any of the other centrality measures studied.
Original languageEnglish
Pages (from-to)556-565
Number of pages10
JournalJournal of Theoretical Biology
Volume263
Issue number4
DOIs
Publication statusPublished - 21 Apr 2010

Keywords

  • centrality indices
  • subgraph centrality
  • protein–protein interactions
  • complex networks
  • matrix functions

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