Individual nodes contribution to the mesoscale of complex networks

Florian Klimm, Javier Borge-Holthoefer, Niels Wessel, Jürgen Kurths, Gorka Zamora-Lopez

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

The analysis of complex networks is devoted to the statistical characterization of the topology of graphs at different scales of organization in order to understand their functionality. While the modular structure of networks has become an essential element to better apprehend their complexity, the efforts to characterize the mesoscale of networks have focused on the identification of the modules rather than describing the mesoscale in an informative manner. Here we propose a framework to characterize the position every node takes within the modular configuration of complex networks and to evaluate their function accordingly. For illustration, we apply this framework to a set of synthetic networks, empirical neural networks, and to the transcriptional regulatory network of the Mycobacterium tuberculosis. We find that the architecture of both neuronal and transcriptional networks are optimized for the processing of multisensory information with the coexistence of well-defined modules of specialized components and the presence of hubs conveying information from and to the distinct functional domains.

Original languageEnglish
Article number125006
JournalNew Journal of Physics
Volume16
DOIs
Publication statusPublished - 2 Dec 2014

    Fingerprint

Keywords

  • community structure
  • genetic regulatory networks
  • network metrics
  • neuronal networks

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Klimm, F., Borge-Holthoefer, J., Wessel, N., Kurths, J., & Zamora-Lopez, G. (2014). Individual nodes contribution to the mesoscale of complex networks. New Journal of Physics, 16, [125006]. https://doi.org/10.1088/1367-2630/16/12/125006