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The Small World Inside Large Metabolic Networks

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  • Andreas Wagner
  • David Fell

Abstract

We analyze the structure of a large metabolic network, that of the energy and biosynthesis metabolism of Escherichia coli. This network is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyze the structure of networks involving hundreds or thousands of components by simple visual inspection is impossible, and a quantitative framework is needed to analyze them. We propose a graph theoretical description of the E. coli metabolic network, a description that we hope will prove useful for other genetic networks. We find that this network is a small world graph, a type of graph observed in a variety of seemingly unrelated areas, such as friendship networks in sociology, the structure of electrical power grids, and the nervous system of C. elegans. Moreover, its connectivity follows a power law, another unusual but by no means rare statistical distribution. This architecture may serve to minimize transition times between metabolic states, and also reflect the evolutionary history of metabolism.

Suggested Citation

  • Andreas Wagner & David Fell, 2000. "The Small World Inside Large Metabolic Networks," Working Papers 00-07-041, Santa Fe Institute.
    • Handle: RePEc:wop:safiwp:00-07-041
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    Citations

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    Cited by:

    1. Petra M. Gleiss & Peter F. Stadler & Andreas Wagner & David A. Fell, 2000. "Small Cycles in Small Worlds," Working Papers 00-10-058, Santa Fe Institute.
    2. Andreas Wagner, 2001. "Estimating Coarse Gene Network Structure from Large-Scale Gene Perturbation Data," Working Papers 01-09-051, Santa Fe Institute.
    3. Marr, Carsten & Hütt, Marc-Thorsten, 2005. "Topology regulates pattern formation capacity of binary cellular automata on graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 641-662.
    4. Serra, Roberto & Villani, Marco & Agostini, Luca, 2004. "On the dynamics of random Boolean networks with scale-free outgoing connections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 665-673.
    5. Adil Akhtar & Tazid Ali, 2015. "Networks in Amino Acids Based on Mutation," Studies in Microeconomics, , vol. 3(2), pages 89-100, December.
    6. Li, Wenyuan & Lin, Yongjing & Liu, Ying, 2007. "The structure of weighted small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 708-718.
    7. How to Reconstruct a Large Genetic Network from n Gene Perturbations in Fewer than n2 Easy Steps, 2001. "How to Reconstruct a Large Genetic Network from," Working Papers 01-09-047, Santa Fe Institute.
    8. Hamidreza Eslami & Ashkan Ebadi & Andrea Schiffauerova, 2013. "Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 99-119, October.
    9. Andrea De Martino & Daniele De Martino & Roberto Mulet & Andrea Pagnani, 2014. "Identifying All Moiety Conservation Laws in Genome-Scale Metabolic Networks," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-11, July.
    10. Andreas Wagner, 2001. "The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes," Working Papers 01-04-022, Santa Fe Institute.

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