Genome-Scale Algorithm Design

Presenting the fundamental algorithms and data structures that power bioinformatics workflows, this book covers a range of topics from the foundations of sequence analysis (alignments and hidden Markov models) to classical index structures (k-mer indexes, suffix arrays, and suffix trees), Burrows–Wheeler indexes, graph algorithms, network flows, and a number of advanced omics applications. The chapters feature numerous examples, algorithm visualizations, and exercises, providing graduate students, researchers, and practitioners with a powerful algorithmic toolkit for the applications of high-throughput sequencing. An accompanying website (www.genome-scale.info) offers supporting teaching material. The second edition strengthens the toolkit by covering minimizers and other advanced data structures and their use in emerging pangenomics approaches.

• Provides an integrated picture of the fundamental algorithms and data structures that power modern sequence analysis, covering a range of topics including foundations, classical index structures, and Burrows–Wheeler indexes
• Chapters feature numerous examples, algorithm visualizations, problems, and end-of-chapter exercises, providing students with a powerful toolkit for the emerging applications of high-throughput sequencing
• Presents only the minimum data structures necessary so that students are not burdened with technical results and can also focus on more conceptual algorithm design questions