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Algorithms for Next-Generation Sequencing Data : Techniques, Approaches, and Applications / edited by Mourad Elloumi.
- Format:
- Book
- Series:
- Computer Science (Springer-11645)
- Language:
- English
- Subjects (All):
- Bioinformatics.
- Biomathematics.
- Algorithms.
- Computational Biology/Bioinformatics.
- Mathematical and Computational Biology.
- Algorithm Analysis and Problem Complexity.
- Local Subjects:
- Computational Biology/Bioinformatics.
- Mathematical and Computational Biology.
- Bioinformatics.
- Algorithm Analysis and Problem Complexity.
- Physical Description:
- 1 online resource (XIII, 355 pages) : 108 illustrations, 3 illustrations in color
- Edition:
- First edition 2017.
- Contained In:
- Springer eBooks
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2017.
- System Details:
- text file PDF
- Summary:
- The 14 contributed chapters in this book survey the most recent developments in high-performance algorithms for NGS data, offering fundamental insights and technical information specifically on indexing, compression and storage; error correction; alignment; and assembly. The book will be of value to researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-59826-0
- 9783319598260
- Access Restriction:
- Restricted for use by site license.
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