Literature DB >> 11019047

Mean-field solution of the small-world network model.

M E Newman1, C Moore, D J Watts.   

Abstract

The small-world network model is a simple model of the structure of social networks, which possesses characteristics of both regular lattices and random graphs. The model consists of a one-dimensional lattice with a low density of shortcuts added between randomly selected pairs of points. These shortcuts greatly reduce the typical path length between any two points on the lattice. We present a mean-field solution for the average path length and for the distribution of path lengths in the model. This solution is exact in the limit of large system size and either a large or small number of shortcuts.

Mesh:

Year:  2000        PMID: 11019047     DOI: 10.1103/PhysRevLett.84.3201

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  15 in total

Review 1.  Complex networks and simple models in biology.

Authors:  Eric de Silva; Michael P H Stumpf
Journal:  J R Soc Interface       Date:  2005-12-22       Impact factor: 4.118

2.  Social network analysis of biomedical research collaboration networks in a CTSA institution.

Authors:  Jiang Bian; Mengjun Xie; Umit Topaloglu; Teresa Hudson; Hari Eswaran; William Hogan
Journal:  J Biomed Inform       Date:  2014-02-18       Impact factor: 6.317

3.  Modeling early lexico-semantic network development: Perceptual features matter most.

Authors:  Ryan Peters; Arielle Borovsky
Journal:  J Exp Psychol Gen       Date:  2019-04

4.  Functional network inference of the suprachiasmatic nucleus.

Authors:  John H Abel; Kirsten Meeker; Daniel Granados-Fuentes; Peter C St John; Thomas J Wang; Benjamin B Bales; Francis J Doyle; Erik D Herzog; Linda R Petzold
Journal:  Proc Natl Acad Sci U S A       Date:  2016-04-04       Impact factor: 11.205

5.  SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

Authors:  Vito Paolo Pastore; Aleksandar Godjoski; Sergio Martinoia; Paolo Massobrio
Journal:  Neuroinformatics       Date:  2018-01

6.  Modularity and anti-modularity in networks with arbitrary degree distribution.

Authors:  Arend Hintze; Christoph Adami
Journal:  Biol Direct       Date:  2010-05-06       Impact factor: 4.540

7.  Small-world network models of intercellular coupling predict enhanced synchronization in the suprachiasmatic nucleus.

Authors:  Christina Vasalou; Erik D Herzog; Michael A Henson
Journal:  J Biol Rhythms       Date:  2009-06       Impact factor: 3.182

8.  Methods for generating complex networks with selected structural properties for simulations: a review and tutorial for neuroscientists.

Authors:  Brenton J Prettejohn; Matthew J Berryman; Mark D McDonnell
Journal:  Front Comput Neurosci       Date:  2011-03-10       Impact factor: 2.380

9.  Measuring predictability of autonomous network transitions into bursting dynamics.

Authors:  Sima Mofakham; Michal Zochowski
Journal:  PLoS One       Date:  2015-04-09       Impact factor: 3.240

10.  Network 'small-world-ness': a quantitative method for determining canonical network equivalence.

Authors:  Mark D Humphries; Kevin Gurney
Journal:  PLoS One       Date:  2008-04-30       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.