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A Reinforcement Learning Based Approach to Multiple Sequence Alignment

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Soft Computing Applications (SOFA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 634))

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Abstract

Multiple sequence alignment plays an important role in comparative genomic sequence analysis, being one of the most challenging problems in bioinformatics. This problem refers to the process of arranging the primary sequences of DNA, RNA or protein to identify regions of similarity that may be a consequence of functional, structural or evolutionary relationships between the sequences. In this paper we tackle multiple sequence alignment from a computational perspective and we introduce a novel approach, based on reinforcement learning, for addressing it. The experimental evaluation is performed on several DNA data sets, two of which contain human DNA sequences. The efficiency of our algorithm is shown by the obtained results, which prove that our technique outperforms other methods existing in the literature and which also indicate the potential of our proposal.

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Acknowledgment

This work was supported by a grant of the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PN-II-RU-TE-2014-4-0082.

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Authors and Affiliations

  1. Faculty of Mathematics and Computer Science, Babeş-Bolyai University, 1, M. Kogălniceanu Street, 400084, Cluj-Napoca, Romania

    Ioan-Gabriel Mircea, Iuliana Bocicor & Gabriela Czibula

Authors
  1. Ioan-Gabriel Mircea
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  2. Iuliana Bocicor
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  3. Gabriela Czibula
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Corresponding authors

Correspondence to Ioan-Gabriel Mircea , Iuliana Bocicor or Gabriela Czibula .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. University of Canberra, Canberra, South Australia, Australia

    Lakhmi C. Jain

  3. Universitatea Aurel Vlaicu Din Arad, Arad, Romania

    Marius Mircea Balas

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Mircea, IG., Bocicor, I., Czibula, G. (2018). A Reinforcement Learning Based Approach to Multiple Sequence Alignment. In: Balas, V., Jain, L., Balas, M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-62524-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-62524-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62523-2

  • Online ISBN: 978-3-319-62524-9

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