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An optimal algorithm for counting network motifs

Author

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  • Itzhack, Royi
  • Mogilevski, Yelena
  • Louzoun, Yoram

Abstract

Network motifs are small connected sub-graphs occurring at significantly higher frequencies in a given graph compared with random graphs of similar degree distribution. Recently, network motifs have attracted attention as a tool to study networks microscopic details. The commonly used algorithm for counting small-scale motifs is the one developed by Milo et al. This algorithm is extremely costly in CPU time and actually cannot work on large networks, consisting of more than 100,000 edges on current CPUs.

Suggested Citation

  • Itzhack, Royi & Mogilevski, Yelena & Louzoun, Yoram, 2007. "An optimal algorithm for counting network motifs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 482-490.
    • Handle: RePEc:eee:phsmap:v:381:y:2007:i:c:p:482-490
    DOI: 10.1016/j.physa.2007.02.102
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    Citations

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    Cited by:

    1. Takaaki Ohnishi & Hideki Takayasu & Misako Takayasu, 2010. "Network motifs in an inter-firm network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(2), pages 171-180, December.
    2. Marius Agasse-Duval & Steve Lawford, 2019. "Subgraphs and Motifs in a Dynamic Airline Network," Working Papers hal-02017122, HAL.
    3. Yanxin Liu & Huajiao Li & Jianhe Guan & Xueyong Liu & Yajie Qi, 2019. "The role of the world’s major steel markets in price spillover networks: an analysis based on complex network motifs," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 697-720, December.

    More about this item

    Keywords

    Graph; Networks; Motif; Algorithm;
    All these keywords.

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