Designed for a one or two semester senior undergraduate or graduate bioinformatics course, Statistical Bioinformatics 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 and SAS code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics.

Integrates biological, statistical and computational concepts

Inclusion of R & SAS code

Provides coverage of complex statistical methods in context with applications in bioinformatics

Exercises and examples aid teaching and learning presented at the right level

Bayesian methods and the modern multiple testing principles in one convenient book

Product Description

Provides coverage of complex statistical methods in context with applications in bioinformatics. This book integrates biological, statistical and computational concepts. It includes R & SAS code. It presents Bayesian methods and the modern multiple testing principles.

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