11. Introduction to Graphical Modelling

  1. Michael P. H. Stumpf3,
  2. David J. Balding4 and
  3. Mark Girolami5
  1. Marco Scutari1 and
  2. Korbinian Strimmer2

Published Online: 12 SEP 2011

DOI: 10.1002/9781119970606.ch11

Handbook of Statistical Systems Biology

Handbook of Statistical Systems Biology

How to Cite

Scutari, M. and Strimmer, K. (2011) Introduction to Graphical Modelling, 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.ch11

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

    UCL Genetics Institute (UGI), University College London, UK

  2. 2

    Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany

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:

  • graphical models;
  • random variables;
  • Markov and Bayesian networks;
  • fitting graphical models;
  • parameter learning;
  • score-based algorithms;
  • ASIA Bayesian network factorisation;
  • graphical model inference

Summary

This chapter contains sections titled:

  • Graphical structures and random variables

  • Learning graphical models

  • Inference on graphical models

  • Application of graphical models in systems biology

  • References