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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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
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