Computational Genome Analysis : An Introduction

Contents: Acknowledgements. 1. Biology in a nutshell. 2. Words. 3. Word distributions and occurrences. 4. Physical mapping of DNA. 5. Genome rearrangements. 6. Sequence alignment. 7. Rapid Alignment Methods: FASTA and BLAST. 8. DNA Sequence Assembly. 9. Signals in DNA. 10. Similarity, distance and clustering. 11. Measuring expression of genome information. 12. Inferring the past: phylogenetic trees. 13. Genetic variation in populations. 14. Comparative genomics. Glossary: 1. A brief introduction to R. 2. Internet bioinformatics resources. 3. Miscellaneous data.

"Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. This book is appropriate for a one-semester course for advanced graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.
   
This book features:  

• Topics organized around biological problems, such as sequence alignment and assembly, DNA Signals, analysis of gene expression and human genetic variation.
• Presentation of fundamentals of probability, statistics and algorithms.
• Implementation of computational methods with numerous examples based upon the R statistics package.
• Extensive descriptions and explanations to complement the analytical development.
• More than 100 illustrations and diagrams (15 in color) to reinforce concepts and present key results from the primary literature.
• Exercises at the end of chapters."