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. 2010 Feb 19;38(11):3523–3532. doi: 10.1093/nar/gkq045

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© The Author(s) 2010. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 1. — A Bayesian network to model gene response with gene categories. Gene categories, or terms (, ellipses) can be either on or off. Terms that are on activate the hidden state (, rectangles) of all genes annotated to them, the other genes remain off. The observed states (, diamonds) of the genes are noisy observations of their true hidden state. The parameters of the model (light gray nodes) are the prior probability of each term to be active, , the false positive rate, and the false negative rate, .

Inline graphic — A Bayesian network to model gene response with gene categories. Gene categories, or terms (, ellipses) can be either on or off. Terms that are on activate the hidden state (, rectangles) of all genes annotated to them, the other genes remain off. The observed states (, diamonds) of the genes are noisy observations of their true hidden state. The parameters of the model (light gray nodes) are the prior probability of each term to be active, , the false positive rate, and the false negative rate, .