Statistical Bioinformatics: with R (Hardcover)

Sunil K. Mathur

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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 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.

Ch 1: Introduction

Ch 2: Genomics

Ch 3: Probability and Statistical Theory

Ch 4: Special Distributions, Properties and Applications

Ch 5: Statistical Inference and Applications

Ch 6: Nonparametric Statistics

Ch 7: Bayesian Statistics

Ch 8: Markov Chain, Monte Carlo

Ch 9: Analysis of Variance

Ch 10: Design of Experiments

Ch 11: Multiple Testing of Hypotheses