Algorithms for Next-Generation Sequencing Data
Techniques, Approaches, and Applications
Editors: Elloumi, Mourad (Ed.)
Free Preview- First consolidated description of techniques and applications
- Key technology will help to decode life's mysteries, detect pathogens, make better crops, and improve quality of life
- Valuable for researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences
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- About this book
-
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.
- Table of contents (14 chapters)
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Algorithms for Indexing Highly Similar DNA Sequences
Pages 3-39
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Full-Text Indexes for High-Throughput Sequencing
Pages 41-75
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Searching and Indexing Circular Patterns
Pages 77-90
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De Novo NGS Data Compression
Pages 91-115
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Cloud Storage-Management Techniques for NGS Data
Pages 117-128
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Table of contents (14 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Algorithms for Next-Generation Sequencing Data
- Book Subtitle
- Techniques, Approaches, and Applications
- Editors
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- Mourad Elloumi
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-59826-0
- DOI
- 10.1007/978-3-319-59826-0
- Hardcover ISBN
- 978-3-319-59824-6
- Softcover ISBN
- 978-3-319-86710-6
- Edition Number
- 1
- Number of Pages
- XIII, 355
- Number of Illustrations
- 105 b/w illustrations, 3 illustrations in colour
- Topics
