Genome-Scale Algorithm Design

Biological Sequence Analysis in the Era of High-Throughput Sequencing

Nonfiction, Science & Nature, Science, Biological Sciences, Genetics, Mathematics
Cover of the book Genome-Scale Algorithm Design by Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu, Cambridge University Press
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Author: Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu ISBN: 9781316342893
Publisher: Cambridge University Press Publication: May 7, 2015
Imprint: Cambridge University Press Language: English
Author: Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu
ISBN: 9781316342893
Publisher: Cambridge University Press
Publication: May 7, 2015
Imprint: Cambridge University Press
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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