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Algorithms for Next-Generation Sequencing Data pp 3–39Cite as

Algorithms for Indexing Highly Similar DNA Sequences

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Abstract

The availability of numerical data grows from one day to the other in an extraordinary way. This is the case for DNA sequences produced by new technologies of high-throughput Next Generation Sequencing (NGS). Hence, it is possible to sequence several genomes of organisms and a project (http://www.1000genomes.org) now provide about 2500 individual human genomes (sequences of more than three billion characters (A, C, G, T).

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Notes

  1. 1.

    http://www.1000genomes.org.

  2. 2.

    In this exposition all logarithms are in base 2 unless stated otherwise.

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Author information

Authors and Affiliations

  1. Laboratory of Technologies of Information and Communication and Electrical Engineering (LaTICE), Tunis, Tunisia

    Nadia Ben Nsira

  2. University of Tunis-El Manar, Tunis, Tunisia

    Nadia Ben Nsira & Mourad Elloumi

  3. The Computer Science, Information Processing and Systems Laboratory (LITIS), EA 4108, University of Rouen-Normandy, Normandy, France

    Nadia Ben Nsira

  4. LITIS, EA 4108, University of Rouen-Normandy, Normandy, France

    Thierry Lecroq

  5. LaTICE, Tunis, Tunisia

    Mourad Elloumi

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  1. Nadia Ben Nsira
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    Mourad Elloumi

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Nsira, N.B., Lecroq, T., Elloumi, M. (2017). Algorithms for Indexing Highly Similar DNA Sequences. In: Elloumi, M. (eds) Algorithms for Next-Generation Sequencing Data. Springer, Cham. https://doi.org/10.1007/978-3-319-59826-0_1

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