Introduction to Graphical Modelling

Details Introduction to Graphical Modelling Introduction to Graphical Modelling

2010-05-06

arxiv.org/abs/1005.1036v3

Statistics

Machine Learning

Handbook of Statistical Systems Biology (D. Balding, M. Stumpf, M. Girolami, eds.), Wiley. 21 pages

Scientific paper

The aim of this chapter is twofold. In the first part we will provide a brief overview of the mathematical and statistical foundations of graphical models, along with their fundamental properties, estimation and basic inference procedures. In particular we will develop Markov networks (also known as Markov random fields) and Bayesian networks, which comprise most past and current literature on graphical models. In the second part we will review some applications of graphical models in systems biology.

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