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An Improved Algorithm for Fast and Accurate Classification of Sequences

  • Conference paper
Beyond Databases, Architectures, and Structures (BDAS 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 424))

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Abstract

Understanding of biocenosis derived from environmental samples can help understanding the relationships between organisms and the environmental conditions of their occurrence. Therefore, the classification of DNA fragments that are selected from different places is an important issue in many studies. In this paper we report how to improve (in terms of speed and qualification accuracy) the algorithm of fast and accurate classification of sequences (FACS).

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Author information

Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Jolanta Kawulok & Sebastian Deorowicz

Authors
  1. Jolanta Kawulok
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  2. Sebastian Deorowicz
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Corresponding author

Correspondence to Jolanta Kawulok .

Editor information

Editors and Affiliations

  1. Silesian University of Technology Inst. Computing Science, Gliwice, Poland

    Stanislaw Kozielski

  2. Silesian University of Technology Institute of Informatics, Gliwice, Poland

    Dariusz Mrozek

  3. Silesian University of Technology, Gliwice, Poland

    Pawel Kasprowski

  4. Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Silesian University of Technology, Gliwice,, Poland

    Daniel Kostrzewa

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© 2014 Springer International Publishing Switzerland

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Kawulok, J., Deorowicz, S. (2014). An Improved Algorithm for Fast and Accurate Classification of Sequences. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures, and Structures. BDAS 2014. Communications in Computer and Information Science, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-06932-6_32

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  • DOI: https://doi.org/10.1007/978-3-319-06932-6_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06931-9

  • Online ISBN: 978-3-319-06932-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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