Getting Started in Probabilistic Graphical Models

Edoardo M. Airoldi
2007 PLoS Computational Biology  
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.
doi:10.1371/journal.pcbi.0030252 pmid:18069887 pmcid:PMC2134967 fatcat:ja62f3h3tnbpfmmelkntaqr624