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Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications.
Designed for a one or two-semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications.
The inclusion of R & SAS code as well as the development of advanced methodologies such as Bayesian and Markov models provide students with the important foundation needed to conduct bioinformatics.
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Integrates biological, statistical, and computational concepts
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Inclusion of R & SAS code
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Provides coverage of complex statistical methods in context with applications in bioinformatics
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Exercises and examples aid teaching and learning presented at the right level
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Bayesian methods and the modern multiple testing principles in one convenient book
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Sathiabalan
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