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Motif Analysis

  • Living reference work entry
  • First Online:
Encyclopedia of Social Network Analysis and Mining

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Synonyms

Subgraph count; Subgraph evolution; Subgraph mining

Glossary

Local Topology:

Parts of the network graph in the close distance (typically, 1 up to 2 links) from given node

Network Motifs:

Recurrent and statistically significant subgraphs of given graph G

Network Sampling:

Picking (randomly or using chosen heuristics) a number of representative subgraphs contained in given network graph G

SNA:

Social network analysis

Subgraph Count:

A procedure for enumerating all given subgraphs (e.g., four-node subgraphs) of graph G

Subgraph:

Of a graph G is a graph whose node set is a subset of that of G and whose edge set is a subset of that of G

TSP:

Triad significance profile

Definition

Complex networks, both biological and engineered, were analyzed with respect to the so-called network motifs (Milo et al. 2002). They are small subgraphs (usually of 3 up to 7 nodes in size – due to prohibitive computational cost in the case of enumerating all larger subgraphs in complex networks) which...

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References

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Authors and Affiliations

  1. Institute of Computer Science, Wroclaw, University of Technology, Wroclaw, Poland

    Krzysztof Juszczyszyn

Authors
  1. Krzysztof Juszczyszyn
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Corresponding author

Correspondence to Krzysztof Juszczyszyn .

Editor information

Editors and Affiliations

  1. Computer Science, University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

  2. University of Calgary Computer Science, Calgary, Canada

    Jon Rokne

Section Editor information

  1. Department of Computational Intelligence, Wrocław University of Science and Technology, Wrocław, Poland

    Przemysław Kazienko

  2. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

    Jaroslaw Jankowski

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Juszczyszyn, K. (2017). Motif Analysis. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_238-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7163-9_238-1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7163-9

  • Online ISBN: 978-1-4614-7163-9

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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