14. Random Graph Models and Their Application to Protein–Protein Interaction Networks

  1. Michael P. H. Stumpf3,
  2. David J. Balding4 and
  3. Mark Girolami5
  1. Desmond J. Higham1 and
  2. Nataša Pržulj2

Published Online: 12 SEP 2011

DOI: 10.1002/9781119970606.ch14

Handbook of Statistical Systems Biology

Handbook of Statistical Systems Biology

How to Cite

Higham, D. J. and Pržulj, N. (2011) Random Graph Models and Their Application to Protein–Protein Interaction Networks, in Handbook of Statistical Systems Biology (eds M. P. H. Stumpf, D. J. Balding and M. Girolami), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781119970606.ch14

Editor Information

  1. 3

    Division of Molecular Biosciences, Imperial College London, UK

  2. 4

    Institute of Genetics, University College London, UK

  3. 5

    Department of Statistical Science, University College London, UK

Author Information

  1. 1

    Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK

  2. 2

    Department of Computing, Imperial College London, UK

Publication History

  1. Published Online: 12 SEP 2011
  2. Published Print: 21 OCT 2011

ISBN Information

Print ISBN: 9780470710869

Online ISBN: 9781119970606

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Keywords:

  • random graph model development;
  • protein–protein interaction (PPI);
  • Network Science;
  • proteins of ‘lock’ group;
  • genes and proteins;
  • range-dependent graphs

Summary

This chapter contains sections titled:

  • Background and motivation

  • What do we want from a PPI network?

  • PPI network models

  • Range-dependent graphs

  • Summary

  • References