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171005 ||| eng |
| 020 |
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|a 9783319598260
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| 100 |
1 |
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|a Elloumi, Mourad
|e [editor]
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| 245 |
0 |
0 |
|a Algorithms for Next-Generation Sequencing Data
|h Elektronische Ressource
|b Techniques, Approaches, and Applications
|c edited by Mourad Elloumi
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a XIII, 355 p. 108 illus., 3 illus. in color
|b online resource
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| 653 |
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|a Bioinformatics
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| 653 |
|
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|a Computational and Systems Biology
|
| 653 |
|
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|a Mathematical and Computational Biology
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| 653 |
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|a Algorithms
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| 653 |
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|a Biomathematics
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
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|b Springer
|a Springer eBooks 2005-
|
| 028 |
5 |
0 |
|a 10.1007/978-3-319-59826-0
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-59826-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 570,113
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| 082 |
0 |
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|a 570,285
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| 520 |
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|a 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
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