Algorithms for Next-Generation Sequencing Data

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Cover of 'Algorithms for Next-Generation Sequencing Data'

Table of Contents

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Book Overview
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Chapter 1 Algorithms for Indexing Highly Similar DNA Sequences
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Chapter 2 Full-Text Indexes for High-Throughput Sequencing
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Chapter 3 Searching and Indexing Circular Patterns
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Chapter 4 De Novo NGS Data Compression
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Chapter 5 Cloud Storage-Management Techniques for NGS Data
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Chapter 6 Probabilistic Models for Error Correction of Nonuniform Sequencing Data
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Chapter 7 DNA-Seq Error Correction Based on Substring Indices
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Chapter 8 Error Correction in Methylation Profiling From NGS Bisulfite Protocols
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Chapter 9 Comparative Assessment of Alignment Algorithms for NGS Data: Features, Considerations, Implementations, and Future
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Chapter 10 CUSHAW Suite: Parallel and Efficient Algorithms for NGS Read Alignment
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Chapter 11 String-Matching and Alignment Algorithms for Finding Motifs in NGS Data
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Chapter 12 The Contig Assembly Problem and Its Algorithmic Solutions
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Chapter 13 An Efficient Approach to Merging Paired-End Reads and Incorporation of Uncertainties
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Chapter 14 Assembly-Free Techniques for NGS Data

Attention for Chapter 4: De Novo NGS Data Compression

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Gaëtan Benoit, Claire Lemaitre, Guillaume Rizk, Erwan Drezen, Dominique Lavenier. De Novo NGS Data Compression. Mourad Elloumi. Algorithms for Next-Generation Sequencing Data, Springer, pp.91-115, 2017, 978-3-319-59826-0. 〈10.1007/978-3-319-59826-0_4〉. 〈h

HAL Archives-Ouvertes, 08 Dec 2017

Gaëtan Benoit, Claire Lemaitre, Guillaume Rizk, Erwan Drezen, Dominique Lavenier.

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