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Brazilian Symposium on Bioinformatics

BSB 2014: Advances in Bioinformatics and Computational Biology pp 73–82Cite as

A Multi-Objective Evolutionary Algorithm for Improving Multiple Sequence Alignments

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8826))

Abstract

Multiple Sequence Alignments are essential tools for many tasks performed in molecular biology. This paper proposes an efficient, scalable and effective multi-objective evolutionary algorithm to optimize pre-aligned sequences. This algorithm benefits from the great diversity of state-of-the-art algorithms and produces alignments that do not depend on specific sequence features. The proposed method is validated with a database of refined multiple sequence alignments and uses four standard metrics to compare the quality of the results.

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Author information

Authors and Affiliations

  1. Intelligent Systems and Spatial Information Lab., Central University, Colombia

    Wilson Soto

  2. McGill Centre for Bioinformatics, McGill University, Montreal, Canada

    David Becerra

Authors
  1. Wilson Soto
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  2. David Becerra
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Editor information

Editors and Affiliations

  1. Departamento de Ciência de Computação, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Pampulha, 31270-010, Belo Horizonte, MG, Brazil

    Sérgio Campos

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Soto, W., Becerra, D. (2014). A Multi-Objective Evolutionary Algorithm for Improving Multiple Sequence Alignments. In: Campos, S. (eds) Advances in Bioinformatics and Computational Biology. BSB 2014. Lecture Notes in Computer Science(), vol 8826. Springer, Cham. https://doi.org/10.1007/978-3-319-12418-6_10

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  • DOI: https://doi.org/10.1007/978-3-319-12418-6_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12417-9

  • Online ISBN: 978-3-319-12418-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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