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Generating Random Networks and Graphs$
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Ton Coolen, Alessia Annibale, and Ekaterina Roberts

Print publication date: 2017

Print ISBN-13: 9780198709893

Published to Oxford Scholarship Online: May 2017

DOI: 10.1093/oso/9780198709893.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (www.oxfordscholarship.com). (c) Copyright Oxford University Press, 2019. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 22 October 2019

Applications of random graphs

Applications of random graphs

Chapter:
(p.207) 11 Applications of random graphs
Source:
Generating Random Networks and Graphs
Author(s):

A.C.C. Coolen

A. Annibale

E.S. Roberts

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198709893.003.0011

This chapter reviews graph generation techniques in the context of applications. The first case study is power grids, where proposed strategies to prevent blackouts have been tested on tailored random graphs. The second case study is in social networks. Applications of random graphs to social networks are extremely wide ranging – the particular aspect looked at here is modelling the spread of disease on a social network – and how a particular construction based on projecting from a bipartite graph successfully captures some of the clustering observed in real social networks. The third case study is on null models of food webs, discussing the specific constraints relevant to this application, and the topological features which may contribute to the stability of an ecosystem. The final case study is taken from molecular biology, discussing the importance of unbiased graph sampling when considering if motifs are over-represented in a protein–protein interaction network.

Keywords:   Applications, Power grids, Food web, Protein interaction networks, Protein-protein interaction, Motifs, SIR model, Social networks, Bipartite projection, Tailored random graphs

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