Topological generalizations of network motifs

N. Kashtan, S. Itzkovitz, R. Milo, and U. Alon
Phys. Rev. E 70, 031909 – Published 23 September 2004

Abstract

Biological and technological networks contain patterns, termed network motifs, which occur far more often than in randomized networks. Network motifs were suggested to be elementary building blocks that carry out key functions in the network. It is of interest to understand how network motifs combine to form larger structures. To address this, we present a systematic approach to define “motif generalizations”: families of motifs of different sizes that share a common architectural theme. To define motif generalizations, we first define “roles” in a subgraph according to structural equivalence. For example, the feedforward loop triad—a motif in transcription, neuronal, and some electronic networks—has three roles: an input node, an output node, and an internal node. The roles are used to define possible generalizations of the motif. The feedforward loop can have three simple generalizations, based on replicating each of the three roles and their connections. We present algorithms for efficiently detecting motif generalizations. We find that the transcription networks of bacteria and yeast display only one of the three generalizations, the multi-output feedforward generalization. In contrast, the neuronal network of C. elegans mainly displays the multi-input generalization. Forward-logic electronic circuits display a multi-input, multi-output hybrid. Thus, networks which share a common motif can have very different generalizations of that motif. Using mathematical modeling, we describe the information processing functions of the different motif generalizations in transcription, neuronal, and electronic networks.

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  • Received 8 March 2004

DOI:https://doi.org/10.1103/PhysRevE.70.031909

©2004 American Physical Society

Authors & Affiliations

N. Kashtan1,2, S. Itzkovitz1,3, R. Milo1,3, and U. Alon1,3

  • 1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel 76100
  • 2Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel 76100
  • 3Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel 76100

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Issue

Vol. 70, Iss. 3 — September 2004

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