Statistical bioinformatics with R
Author(s)
Bibliographic Information
Statistical bioinformatics with R
Academic Press/Elsevier, c2010
- : hbk
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Note
Includes bibliographical references (p. 305-314) and index
Description and Table of Contents
Description
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 methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics.
Table of Contents
1. Introduction2. Genomics3. Probability and Statistical Theory4. Special Distributions, Properties and Applications5. Statistical Inference and Applications6. Nonparametric Statistics7. Bayesian Statistics8. Markov Chain, Monte Carlo9. Analysis of Variance10. Design of Experiments11. Multiple Testing of Hypotheses
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