Functional cartography of complex metabolic networks

Roger Guimerà, Luis A.Nunes Amaral*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2105 Scopus citations

Abstract

High-throughput techniques are leading to an explosive growth in the size of biological databases and creating the opportunity to revolutionize our understanding of life and disease. Interpretation of these data remains, however, a major scientific challenge. Here, we propose a methodology that enables us to extract and display information contained in complex networks. Specifically, we demonstrate that we can find functional modules in complex networks, and classify nodes into universal roles according to their pattern of intra- and inter-module connections. The method thus yields a 'cartographic representation' of complex networks. Metabolic networks are among the most challenging biological networks and, arguably, the ones with most potential for immediate applicability. We use our method to analyse the metabolic networks of twelve organisms from three different superkingdoms. We find that, typically, 80% of the nodes are only connected to other nodes within their respective modules, and that nodes with different roles are affected by different evolutionary constraints and pressures. Remarkably, we find that metabolites that participate in only a few reactions but that connect different modules are more conserved than hubs whose links are mostly within a single module.

Original languageEnglish (US)
Pages (from-to)895-900
Number of pages6
JournalNature
Volume433
Issue number7028
DOIs
StatePublished - Feb 24 2005

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Functional cartography of complex metabolic networks'. Together they form a unique fingerprint.

Cite this