On the motif distribution in random block-hierarchical networks

V. A. Avetisov 1, S. K. Nechaev 2, 3, 4, A. B. Shkarin 5

Physica A: Statistical Mechanics and its Applications 389, 24 (2010) 5895-5902

The distribution of motifs in random hierarchical networks defined by nonsymmetric random block–hierarchical adjacency matrices, is constructed for the first time. According to the classification of U. Alon et al of network superfamilies by their motifs distributions, our artificial directed random hierarchical networks falls into the superfamily of natural networks to which the class of neuron networks belongs. This is the first example of « handmade » networks with the motifs distribution as in a special class of natural networks of essential biological importance.

  • 1. The Semenov Institute of Chemical Physics,
    Russian Academy of Sciences
  • 2. Laboratoire de Physique Théorique et Modèles Statistiques (LPTMS),
    CNRS : UMR8626 – Université Paris XI – Paris Sud
  • 3. P. N. Lebedev Physical Institute,
    Russian Academy of Science
  • 4. JV Poncelet Laboratory,
    Independant University
  • 5. Moscow Institute of Physics and Technology (MIPT),
    Moscow Institute of Physics and Technology
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