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 language | English (US) |
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Pages (from-to) | 895-900 |
Number of pages | 6 |
Journal | Nature |
Volume | 433 |
Issue number | 7028 |
DOIs | |
State | Published - Feb 24 2005 |
Funding
Acknowledgements We thank L. Broadbelt, V. Hatzimanikatis, A. A. Moreira, E. T. Papoutsakis, M. Sales-Pardo and D. B. Stouffer for discussions and suggestions, and H. Ma and A. P. Zeng for providing us with their metabolic networks’ database. R.G. thanks the Fulbright Program and the Spanish Ministry of Education, Culture & Sports. L.A.N.A. acknowledges the support of a Searle Leadership Fund Award and of a NIH/NIGMS K-25 award. Acknowledgements We thank N. Roggli for drawings; C. Niyogi and M. Havaux for the npq4 mutant; C. Fankhauser for transformation vectors and help with Arabidopsis; C. Bréhélin and F. Kessler (Plant Survival NCCR) for help with the protoplast transformation experiments; B. Genty and M. Goldschmidt-Clermont for discussions; M. Péan, A. Beyly and the GRAP team (CEA Cadarache) for support in growing plants under controlled conditions; and B. Delessert for assistance in the phytotron. F.B. was supported by a long-term EMBO fellowship. This work was supported by a grant from the Swiss National Foundation.
ASJC Scopus subject areas
- General