Extracting the hierarchical organization of complex systems

Marta Sales-Pardo, Roger Guimerà, André A. Moreira, Luís A. Nunes Amaral*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

367 Scopus citations

Abstract

Extracting understanding from the growing "sea" of biological and socioeconomic data is one of the most pressing scientific challenges facing us. Here, we introduce and validate an unsupervised method for extracting the hierarchical organization of complex biological, social, and technological networks. We define an ensemble of hierarchically nested random graphs, which we use to validate the method. We then apply our method to real-world networks, including the air-transportation network, an electronic circuit an e-mail exchange network, and metabolic networks. Our analysis of model and real networks demonstrates that our method extracts an accurate multiscale representation of a complex system.

Original languageEnglish (US)
Pages (from-to)15224-15229
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume104
Issue number39
DOIs
StatePublished - Sep 25 2007

Keywords

  • Cellular metabolism
  • Complex networks
  • Multiscale representation

ASJC Scopus subject areas

  • General

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