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Establish the Expected Number of Injective Motifs on Unlabeled Graphs Through Analytical Models

  • Emanuele Martorana
  • Giovanni Micale
  • Alfredo Ferro
  • Alfredo PulvirentiEmail author
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 882)

Abstract

Network motifs have a central role in explaining the functionality of complex systems. Establishing motif significance requires the computation of the expected number of their occurrences according to a random graph model. Few models have been proposed to analytically derive the expected number of non-induced occurrences of a motif. In this paper we present an analytical model to compute the expected number of occurrences of induced motifs in unlabeled graphs. We will illustrate two different algorithms for computing the occurrence probability of induced motifs. We evaluate the performance of our algorithms for calculating the expected number of induced motifs with up to 10 nodes.

Keywords

Injective motifs Networks Random graphs Analytical models 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Emanuele Martorana
    • 1
  • Giovanni Micale
    • 2
  • Alfredo Ferro
    • 2
  • Alfredo Pulvirenti
    • 2
    Email author
  1. 1.Department of Physics and AstronomyUniversity of CataniaCataniaItaly
  2. 2.Department of Clinical and Experimental MedicineUniversity of CataniaCataniaItaly

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