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Discovering motifs to fingerprint multi-layer networks: a case study on the connectome of C. Elegans

Author

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  • Deepak Sharma

    (Christian-Albrechts Universität zu Kiel)

  • Matthias Renz

    (Christian-Albrechts Universität zu Kiel)

  • Philipp Hövel

    (Saarland University)

Abstract

Motif discovery is a powerful and insightful method to quantify network structures and explore their function. As a case study, we present a comprehensive analysis of regulatory motifs in the connectome of the model organism Caenorhabditis elegans (C. elegans). Leveraging the Efficient Subgraph Counting Algorithmic PackagE (ESCAPE) algorithm, we identify network motifs in the multi-layer nervous system of C. elegans and link them to functional circuits. We further investigate motif enrichment within signal pathways and benchmark our findings with random networks of similar size and link density. Our findings provide valuable insights into the organization of the nerve net of this well-documented organism and can be easily transferred to other species and disciplines alike. Graphical abstract

Suggested Citation

  • Deepak Sharma & Matthias Renz & Philipp Hövel, 2025. "Discovering motifs to fingerprint multi-layer networks: a case study on the connectome of C. Elegans," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 98(1), pages 1-15, January.
    • Handle: RePEc:spr:eurphb:v:98:y:2025:i:1:d:10.1140_epjb_s10051-024-00848-4
    DOI: 10.1140/epjb/s10051-024-00848-4
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    References listed on IDEAS

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    1. Gang Yan & Petra E. Vértes & Emma K. Towlson & Yee Lian Chew & Denise S. Walker & William R. Schafer & Albert-László Barabási, 2017. "Network control principles predict neuron function in the Caenorhabditis elegans connectome," Nature, Nature, vol. 550(7677), pages 519-523, October.
    2. M.D. Nelson & N.F. Trojanowski & J.B. George-Raizen & C.J. Smith & C.-C. Yu & C. Fang-Yen & D.M. Raizen, 2013. "The neuropeptide NLP-22 regulates a sleep-like state in Caenorhabditis elegans," Nature Communications, Nature, vol. 4(1), pages 1-10, December.
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