Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before - as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data?

Algorithms for Next-Generation Sequencing 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. In addition to offering an in-depth description of the algorithms for processing sequencing data, it also presents useful case studies describing the applications of this technology.

About the Author
Wing-Kin Sung

Reviews

"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

"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

Book Information
ISBN 9780367657970
Author Wing-Kin Sung
Format Paperback
Page Count 350
Imprint Chapman & Hall/CRC
Publisher Taylor & Francis Ltd
Weight(grams) 453g