Getting started in probabilistic graphical models

Details Getting started in probabilistic graphical models Getting started in probabilistic graphical models

2007-06-14

arxiv.org/abs/0706.2040v2

Airoldi EM (2007) Getting started in probabilistic graphical models. PLoS Comput Biol 3(12): e252

Biology

Quantitative Biology

Quantitative Methods

12 pages, 1 figure

Scientific paper

10.1371/journal.pcbi.0030252

Probabilistic graphical models (PGMs) have become a popular tool for computational analysis of biological data in a variety of domains. But, what exactly are they and how do they work? How can we use PGMs to discover patterns that are biologically relevant? And to what extent can PGMs help us formulate new hypotheses that are testable at the bench? This note sketches out some answers and illustrates the main ideas behind the statistical approach to biological pattern discovery.

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