Finding biologically plausible complex network topologies with a new evolutionary approach for network generation

Gordon Govan, Jakub Chlanda, David Corne, Alexandros O Xenos, Pierluigi Frisco

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We explore the recently introduced Structured Nodes (SN) network model, for which earlier work has shown its capability in matching several topological properties of complex networks. We consider a diverse set of empirical biological complex networks as targets and we use an evolutionary algorithm (EA) approach to identify input for the SN model allowing it to generate networks similar to these targets. We find that by using the EA the structural fit between SN networks and the targets is improved. The combined SN/EA approach is a promising direction to further investigate the growth, properties and behaviour of biological networks.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
Pages59-73
Number of pages15
Volume227
DOIs
Publication statusPublished - 29 Aug 2013
EventInternational Conference on EVOLVE - Leiden, United Kingdom
Duration: 10 Jul 201313 Jul 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume227
ISSN (Print)21945357

Conference

ConferenceInternational Conference on EVOLVE
CountryUnited Kingdom
CityLeiden
Period10/07/1313/07/13

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

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