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Bayesian modeling and inference for motif discovery

By M. Gupta and J.S. Liu


Motif discovery, which focuses on locating short sequence patterns associated with the regulation of genes in a species, leads to a class of statistical missing data problems. These problems are discussed first with reference to a hypothetical model, which serves as a point of departure for more realistic versions of the model. Some general results relating to modeling and inference through the Bayesian and/or frequentist perspectives are presented, and specific problems arising out of the underlying biology are discussed

Publisher: 'Cambridge University Press (CUP)'
Year: 2006
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Provided by: Enlighten
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