2000 character limit reached
Getting started in probabilistic graphical models (0706.2040v2)
Published 14 Jun 2007 in q-bio.QM, cs.LG, physics.soc-ph, stat.ME, and stat.ML
Abstract: 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.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.