Genome-scale algorithm design : biological sequence analysis in the era of high-throughput sequencing / Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu, University of Heisinki, Finland.

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Molecular biology and high-throughput sequencing -- Algorithm design -- Data structures -- Graphs -- Network flows -- Alignments -- Hidden Markov models (HMMs) -- Classical indexes -- Burrows-Wheeler indexes -- Read alignment -- Genome analysis and comparison -- Genome compression -- Fragment assembly -- Genomics -- Transcriptomics -- Metagenomics.

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.