The main audience of the book consists in graduate students in bioinformatics and in graduate students in computer science with a strong interest in molecular biology.
If you use this book as a textbook, or as a source of suggested reading material or exercises in your course, please let us know via email and we will mention your course on this website.
As an example, we describe the content of a 7-week graduate-level course on Algorithms in genome analysis taught at the Department of Computer Science, University of Helsinki, in 2023. Powerpoint slides following the course content can be requested from V.M. The corresponding pdf's are linked below.
- Week 1: Course introduction, Min-hashing and minimizers, Sections 3.5, 11.3.6; Basics of molecular biology, parts 1-2,Basics of molecular biology, part 3, Chapter 1 (and other sources)
- Week 2: Haplotype assembly, Section 14.1; Dynamic programming for various alignment models, Sections 6.1, 6.4-6.4.3
- Week 3: Shortest detour, LCS, sparse DP, affine gaps, co-linear chaining, Sections 6.1.2, 6.2, 6.4.4, 6.4.5, 16.5; Multiple alignment, Alignment on cyclic graphs, Sections 6.6,6.7
- Week 4: Read alignment, variant calling, BWT indexes, Sections 9.1-9.2.2, 10-10.4.1
- Week 5: Hidden Markov models, Chapter 7; Suffix tree applications, Sections 8.3, 8.3.1, 8.4-8.4.4
- Week 6: Bidirectional BWT and its applications, Sections 9.4, 10.4.2, 11.2, 11.2.1, 13.2.3; Prefix-free parsing and r-index, Sections 12.3, 15.2.2
- Week 7: Haplotype matching and pBWT, Approximate pattern matching in O(kn) time, Sections 14.2, 8.4.5; Guest lecture on Colored de Bruijn graphs, Sections 9.7, 15.1.1