Literature DB >> 20866485

How clustering affects the bond percolation threshold in complex networks.

James P Gleeson1, Sergey Melnik, Adam Hackett.   

Abstract

The question of how clustering (nonzero density of triangles) in networks affects their bond percolation threshold has important applications in a variety of disciplines. Recent advances in modeling highly clustered networks are employed here to analytically study the bond percolation threshold. In comparison to the threshold in an unclustered network with the same degree distribution and correlation structure, the presence of triangles in these model networks is shown to lead to a larger bond percolation threshold (i.e. clustering increases the epidemic threshold or decreases resilience of the network to random edge deletion).

Year:  2010        PMID: 20866485     DOI: 10.1103/PhysRevE.81.066114

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


  13 in total

1.  A network with tunable clustering, degree correlation and degree distribution, and an epidemic thereon.

Authors:  Frank Ball; Tom Britton; David Sirl
Journal:  J Math Biol       Date:  2012-11-16       Impact factor: 2.259

2.  Dynamics on modular networks with heterogeneous correlations.

Authors:  Sergey Melnik; Mason A Porter; Peter J Mucha; James P Gleeson
Journal:  Chaos       Date:  2014-06       Impact factor: 3.642

3.  Epidemic spread in networks: Existing methods and current challenges.

Authors:  Joel C Miller; Istvan Z Kiss
Journal:  Math Model Nat Phenom       Date:  2014-01       Impact factor: 4.157

4.  SIR dynamics in random networks with communities.

Authors:  Jinxian Li; Jing Wang; Zhen Jin
Journal:  J Math Biol       Date:  2018-05-11       Impact factor: 2.259

5.  Cocirculation of infectious diseases on networks.

Authors:  Joel C Miller
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2013-06-20

6.  Effects of heterogeneous and clustered contact patterns on infectious disease dynamics.

Authors:  Erik M Volz; Joel C Miller; Alison Galvani; Lauren Ancel Meyers
Journal:  PLoS Comput Biol       Date:  2011-06-02       Impact factor: 4.475

7.  Beyond clustering: mean-field dynamics on networks with arbitrary subgraph composition.

Authors:  Martin Ritchie; Luc Berthouze; Istvan Z Kiss
Journal:  J Math Biol       Date:  2015-04-17       Impact factor: 2.259

8.  Deciphering the global organization of clustering in real complex networks.

Authors:  Pol Colomer-de-Simón; M Ángeles Serrano; Mariano G Beiró; J Ignacio Alvarez-Hamelin; Marián Boguñá
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

9.  Layer-switching cost and optimality in information spreading on multiplex networks.

Authors:  Byungjoon Min; Sang-Hwan Gwak; Nanoom Lee; K-I Goh
Journal:  Sci Rep       Date:  2016-02-18       Impact factor: 4.379

10.  Breaking of the site-bond percolation universality in networks.

Authors:  Filippo Radicchi; Claudio Castellano
Journal:  Nat Commun       Date:  2015-12-15       Impact factor: 14.919

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.