Statistics Applied to Bioinformatics
by Van Helden, JacquesFormat: Paperback
Pub. Date: 2099-07-01
Publisher(s): Oxford University Press
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Summary
A text based on the author's Masters level course on statistics applied to bioinformatics aimed at graduate students from statistics, bioinformatics and biology. Filling a gap in the current literature, the text includes a rigorous and extensive background in biostatistics, along with detailed explanation of the key biological questions before focusing on the statistical analysis. Including exercises, numerous illustrations, extensive end of chapter summaries and examples of programming in R (a freely availabe statistical package), this is an ideal study text.
Table of Contents
| Contents | |
| Introduction | |
| Statistics and bioinformatics | |
| Scope and approach of the book | |
| Acknowledgements | |
| Supporting material | |
| Warning | |
| Bioinformatics and Biology | |
| Sequence searchers in databases | |
| Gene prediction | |
| Detection of sequence motifs | |
| Comparative genomics | |
| Expression profiles | |
| Networks of interaction | |
| Sequence Analysis | |
| Combinatorial analysis | |
| Descriptive statistics | |
| Elements of probabilities | |
| Theoretical distributions of probabilities | |
| Sampling and estimation | |
| Statistical tests | |
| Hidden Markov Models (HMM) | |
| An information theory perspective | |
| Transcriptome | |
| Introduction to multivariate analysis | |
| Correlation analysis | |
| Regression analysis | |
| Analysis of variance | |
| Unsupervised classification (Clustering | |
| Reduction of dimensionality and visualization | |
| Supervised classification (discriminant analysis) | |
| Genome Evolution | |
| Biochemical Networks | |
| Exercises | |
| Annexes | |
| Formula tables | |
| Index | |
| References | |
| Table of Contents provided by Publisher. All Rights Reserved. |
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