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.
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Veli Mäkinen is a Professor of Computer Science at the University of Helsinki, Finland, where he heads a research group working on genome-scale algorithms as part of the Finnish Center of Excellence in Cancer Genetics Research. He has taught advanced courses on string processing, data compression, biological sequence analysis, along with introductory courses on bioinformatics.
Djamal Belazzougui is a postdoctoral researcher at the University of Helsinki. His research topics include hashing, succinct and compressed data structures and string algorithms.
Fabio Cunial is a postdoctoral researcher at the University of Helsinki. His research focuses on string algorithms and genome analysis.
Alexandru I. Tomescu is a postdoctoral researcher at the University of Helsinki. His current research interests lie at the intersection of computational biology and computer science.
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