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Bayesian modeling in bioinformatics.


Bayesian modeling in bioinformatics.

Ed. by Dipak Dey et al.

CRC Press


440 pages



Chapman & Hall/CRC biostatistics series; 34


Specialists explore the development and application of Bayesian statistical methods in medical research, particularly research related to cancer and other diseases, and to molecular and structural biology. The main focus is on data sets arising from the high-throughput experiments microarray gene expression and phylogenic analysis. The topics include estimation and testing in time-course microarray experiments, Bayesian robust inference for differential gene expression, sparsity priors for predicting interaction between proteins, and Bayesian methods for detecting differently expressed genes.

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Publication:SciTech Book News
Article Type:Book review
Date:Dec 1, 2010
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