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Relevant Cycles In Chemical Reaction Networks

Author

Listed:
  • PETRA M. GLEISS

    (Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria)

  • PETER F. STADLER

    (Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstraße 17, A 1090 Wien, Austria;
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA)

  • ANDREAS WAGNER

    (Dept. of Biology, University of New Mexico, 167A Castetter Hall, Albuquerque, NM-817131-1091, USA;
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA)

  • DAVID A. FELL

    (School of Biological & Molecular Sciences, Oxford Brookes University, Oxford OX3 OBP, UK)

Abstract

We characterize the distributions of short cycles in a large metabolic network previously shown to have small world characteristics and a power law degree distribution. Compared with three classes of random networks, including Erdős–Rényi random graphs and synthetic small world networks of the same connectivity, both the metabolic network and models for the chemical reaction networks of planetary atmospheres have a particularly large number of triangles and a deficit in large cycles. Short cycles reduce the length of detours when a connection is clipped, so we propose that long cycles in metabolism may have been selected against in order to shorten transition times and reduce the likelihood of oscillations in response to external perturbations.

Suggested Citation

  • Petra M. Gleiss & Peter F. Stadler & Andreas Wagner & David A. Fell, 2001. "Relevant Cycles In Chemical Reaction Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 4(02n03), pages 207-226.
    • Handle: RePEc:wsi:acsxxx:v:04:y:2001:i:02n03:n:s0219525901000140
    DOI: 10.1142/S0219525901000140
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    Citations

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    Cited by:

    1. Petra M. Gleiss & Josef Leydold & Peter F. Stadler, 2001. "Circuit Bases of Strongly Connected Digraphs," Working Papers 01-10-056, Santa Fe Institute.
    2. Jeong, Wonhee & Yu, Unjong, 2022. "Effects of quadrilateral clustering on complex contagion," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    3. David L. Alderson, 2008. "OR FORUM---Catching the “Network Science” Bug: Insight and Opportunity for the Operations Researcher," Operations Research, INFORMS, vol. 56(5), pages 1047-1065, October.

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