Literature DB >> 18517465

Communicability in complex networks.

Ernesto Estrada1, Naomichi Hatano.   

Abstract

We propose a new measure of the communicability of a complex network, which is a broad generalization of the concept of the shortest path. According to the new measure, most of the real-world networks display the largest communicability between the most connected (popular) nodes of the network (assortative communicability). There are also several networks with the disassortative communicability, where the most "popular" nodes communicate very poorly to each other. Using this information we classify a diverse set of real-world complex systems into a small number of universality classes based on their structure-dynamic correlation. In addition, the new communicability measure is able to distinguish finer structures of networks, such as communities into which a network is divided. A community is unambiguously defined here as a set of nodes displaying larger communicability among them than to the rest of the nodes in the network.

Year:  2008        PMID: 18517465     DOI: 10.1103/PhysRevE.77.036111

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  93 in total

1.  A sparse structure learning algorithm for Gaussian Bayesian Network identification from high-dimensional data.

Authors:  Shuai Huang; Jing Li; Jieping Ye; Adam Fleisher; Kewei Chen; Teresa Wu; Eric Reiman
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2013-06       Impact factor: 6.226

2.  A transcriptional signature of hub connectivity in the mouse connectome.

Authors:  Ben D Fulcher; Alex Fornito
Journal:  Proc Natl Acad Sci U S A       Date:  2016-01-15       Impact factor: 11.205

3.  Breakdown of the brain's functional network modularity with awareness.

Authors:  Douglass Godwin; Robert L Barry; René Marois
Journal:  Proc Natl Acad Sci U S A       Date:  2015-03-10       Impact factor: 11.205

4.  Network diffusion accurately models the relationship between structural and functional brain connectivity networks.

Authors:  Farras Abdelnour; Henning U Voss; Ashish Raj
Journal:  Neuroimage       Date:  2013-12-30       Impact factor: 6.556

5.  Node accessibility in cortical networks during motor tasks.

Authors:  Mario Chavez; Fabrizio De Vico Fallani; Miguel Valencia; Julio Artieda; Donatella Mattia; Vito Latora; Fabio Babiloni
Journal:  Neuroinformatics       Date:  2013-07

Review 6.  Understanding brain networks and brain organization.

Authors:  Luiz Pessoa
Journal:  Phys Life Rev       Date:  2014-04-18       Impact factor: 11.025

7.  A weighted communicability measure applied to complex brain networks.

Authors:  Jonathan J Crofts; Desmond J Higham
Journal:  J R Soc Interface       Date:  2009-01-13       Impact factor: 4.118

8.  Brain Effective Connectivity Modeling for Alzheimer's Disease by Sparse Gaussian Bayesian Network.

Authors:  Shuai Huang; Jing Li; Jieping Ye; Adam Fleisher; Kewei Chen; Teresa Wu; Eric Reiman
Journal:  KDD       Date:  2011

Review 9.  The structure and dynamics of multilayer networks.

Authors:  S Boccaletti; G Bianconi; R Criado; C I Del Genio; J Gómez-Gardeñes; M Romance; I Sendiña-Nadal; Z Wang; M Zanin
Journal:  Phys Rep       Date:  2014-07-10       Impact factor: 25.600

10.  The intrinsic connectome of the rat amygdala.

Authors:  Oliver Schmitt; Peter Eipert; Konstanze Philipp; Richard Kettlitz; Georg Fuellen; Andreas Wree
Journal:  Front Neural Circuits       Date:  2012-12-11       Impact factor: 3.492

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