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New Error Tolerant Method for Search of Long Repeats in DNA Sequences

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Algorithms for Computational Biology (AlCoB 2016)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9702))

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Abstract

A new method to identify all sufficiently long repeating nucleotide substrings in one or several DNA sequences is proposed. The method based on a specific gauge applied to DNA sequences that guarantees identification of the repeating substrings. The method allows the matching substrings to contain a given level of errors. The gauge is based on the development of a heavily sparse dictionary of repeats, thus drastically accelerating the search procedure. Some biological applications illustrate the method.

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Acknowledgments

This study was supported by a research grant No. 14.Y26.31.0004 from the Government of the Russian Federation (M.G. Sadovsky) and the grant from Russian Ministry of Education and Science to Siberian Federal University, contract No. 1.1462.2014/K (S.P. Tsarev).

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Authors and Affiliations

  1. Siberian Federal University, Kirenskogo, 26, 660074, Krasnoyarsk, Russia

    Sergey P. Tsarev

  2. Institute of Computational Modelling of SB RAS, Akademgorodok, 660036, Krasnoyarsk, Russia

    Michael G. Sadovsky

Authors
  1. Sergey P. Tsarev
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  2. Michael G. Sadovsky
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Corresponding author

Correspondence to Michael G. Sadovsky .

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Editors and Affiliations

  1. CETA-Ciemat, Trujillo, Spain

    María Botón-Fernández

  2. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  3. University of Extremadura, Cáceres, Spain

    Sergio Santander-Jiménez

  4. University of Extremadura, Cáceres, Spain

    Miguel A. Vega-Rodríguez

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Tsarev, S.P., Sadovsky, M.G. (2016). New Error Tolerant Method for Search of Long Repeats in DNA Sequences. In: Botón-Fernández, M., Martín-Vide, C., Santander-Jiménez, S., Vega-Rodríguez, M.A. (eds) Algorithms for Computational Biology. AlCoB 2016. Lecture Notes in Computer Science(), vol 9702. Springer, Cham. https://doi.org/10.1007/978-3-319-38827-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-38827-4_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38826-7

  • Online ISBN: 978-3-319-38827-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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