Algorithms for Next-Generation Sequencing

This book is an invaluable tool for students and researchers in bioinformatics and computational biology, biologists seeking to process and manage the data generated by next-generation sequencing, and as a textbook or a self-study resource.

List of contents

Introduction. Reference Alignment. Genome Assembly. Variation Discovery by Mapping to Reference. RNA-seq. ChIP-seq. Meta-Genomic. Other Technologies.

About the author

Wing-Kin Sung

Summary

This book is an invaluable tool for students and researchers in bioinformatics and computational biology, biologists seeking to process and manage the data generated by next-generation sequencing, and as a textbook or a self-study resource.

Additional text

"With every advance in sequencing technology, existing string algorithms are yet again at their limits and need to be developed further. As a result, a book like this one is sorely needed. It lays out the concepts and approaches both for practical data analysis and for developing algorithms powerful enough to deal with the deluge of sequence data."—Martin Vingron, Max Planck Institute for Molecular Genetics

Product details

• Authors: Wing-Kin Sung, Wing-Kin (National University of Singapore) Sung
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 24.05.2017
• EAN: 9781466565500
• ISBN: 978-1-4665-6550-0
• No. of pages: 350
• Series: Chapman & Hall/CRC Mathematical and Computational Biology; Chapman & Hall/CRC Mathematical and Computational Biology; Chapman & Hall/CRC Computational Biology Series; Chapman & Hall/CRC Computation
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics