Genome-Scale Algorithm Design
Biological Sequence Analysis in the Era of High-Throughput Sequencing

Provides an integrated picture of the latest developments in algorithmic techniques, with numerous worked examples, algorithm visualisations and exercises.

Veli Mäkinen (Author), Djamal Belazzougui (Author), Fabio Cunial (Author), Alexandru I. Tomescu (Author)

9781107078536, Cambridge University Press

Hardback, published 7 May 2015

413 pages, 90 b/w illus. 4 tables 269 exercises
25.3 x 18 x 2.2 cm, 0.96 kg

'A very timely textbook covering many recently established techniques and applications at a level of rigor befitting a computer science audience.' Paul Medvedev, Pennsylvania State University

High-throughput sequencing has revolutionised the field of biological sequence analysis. Its application has enabled researchers to address important biological questions, often for the first time. This book provides an integrated presentation of the fundamental algorithms and data structures that power modern sequence analysis workflows. The topics covered range from the foundations of biological sequence analysis (alignments and hidden Markov models), to classical index structures (k-mer indexes, suffix arrays and suffix trees), Burrows–Wheeler indexes, graph algorithms and a number of advanced omics applications. The chapters feature numerous examples, algorithm visualisations, exercises and problems, each chosen to reflect the steps of large-scale sequencing projects, including read alignment, variant calling, haplotyping, fragment assembly, alignment-free genome comparison, transcript prediction and analysis of metagenomic samples. Each biological problem is accompanied by precise formulations, providing graduate students and researchers in bioinformatics and computer science with a powerful toolkit for the emerging applications of high-throughput sequencing.

Notation
Preface
Part I. Preliminaries: 1. Molecular biology and high-throughput sequencing
2. Algorithm design
3. Data structures
4. Graphs
5. Network flows
Part II. Fundamentals of Biological Sequence Analysis: 6. Alignments
7. Hidden Markov models (HMMs)
Part III. Genome-Scale Index Structures: 8. Classical indexes
9. Burrows–Wheeler indexes
Part IV. Genome-Scale Algorithms: 10. Read alignment
11. Genome analysis and comparison
12. Genome compression
13. Fragment assembly
Part V. Applications: 14. Genomics
15. Transcriptomics
16. Metagenomics
References
Index.

Subject Areas: Biology, life sciences [PS], Mathematics & science [P]