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2012 Detecting local network motifs
Etienne Birmelé
Electron. J. Statist. 6: 908-933 (2012). DOI: 10.1214/12-EJS698

Abstract

Studying the structure of so-called real networks, that is networks obtained from sociological or biological data for instance, has become a major field of interest in the last decade. One way to deal with it is to consider that networks are partially built from small functional units called motifs, which can be found by looking for small subgraphs whose numbers of occurrences in the whole network are surprisingly high. In this article, we propose to define motifs through a local over-representation in the network and develop a statistic to detect them without relying on simulations. We then illustrate the performance of our procedure on simulated and real data, recovering already known biologically relevant motifs. Moreover, we explain how our method gives some information about the respective roles of the vertices in a motif.

Citation

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Etienne Birmelé. "Detecting local network motifs." Electron. J. Statist. 6 908 - 933, 2012. https://doi.org/10.1214/12-EJS698

Information

Published: 2012
First available in Project Euclid: 21 May 2012

zbMATH: 1281.05124
MathSciNet: MR2988433
Digital Object Identifier: 10.1214/12-EJS698

Subjects:
Primary: 62P10
Secondary: 05C90

Keywords: biological network , Network motif , Poisson approximation

Rights: Copyright © 2012 The Institute of Mathematical Statistics and the Bernoulli Society

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