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QuateXelero: An Accelerated Exact Network Motif Detection Algorithm

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  • Sahand Khakabimamaghani
  • Iman Sharafuddin
  • Norbert Dichter
  • Ina Koch
  • Ali Masoudi-Nejad

Abstract

Finding motifs in biological, social, technological, and other types of networks has become a widespread method to gain more knowledge about these networks’ structure and function. However, this task is very computationally demanding, because it is highly associated with the graph isomorphism which is an NP problem (not known to belong to P or NP-complete subsets yet). Accordingly, this research is endeavoring to decrease the need to call NAUTY isomorphism detection method, which is the most time-consuming step in many existing algorithms. The work provides an extremely fast motif detection algorithm called QuateXelero, which has a Quaternary Tree data structure in the heart. The proposed algorithm is based on the well-known ESU (FANMOD) motif detection algorithm. The results of experiments on some standard model networks approve the overal superiority of the proposed algorithm, namely QuateXelero, compared with two of the fastest existing algorithms, G-Tries and Kavosh. QuateXelero is especially fastest in constructing the central data structure of the algorithm from scratch based on the input network.

Suggested Citation

  • Sahand Khakabimamaghani & Iman Sharafuddin & Norbert Dichter & Ina Koch & Ali Masoudi-Nejad, 2013. "QuateXelero: An Accelerated Exact Network Motif Detection Algorithm," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-15, July.
    • Handle: RePEc:plo:pone00:0068073
    DOI: 10.1371/journal.pone.0068073
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    1. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
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    Cited by:

    1. Marius Agasse-Duval & Steve Lawford, 2019. "Subgraphs and Motifs in a Dynamic Airline Network," Working Papers hal-02017122, HAL.
    2. Luo, Jiawei & Li, Guanghui & Song, Dan & Liang, Cheng, 2014. "CombiMotif: A new algorithm for network motifs discovery in protein–protein interaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 309-320.
    3. Feng, Pihu & Lu, Xin & Gong, Zaiwu & Sun, Duoyong, 2021. "A case study of the pyramid scheme in China based on communication network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

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