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MEMSA: A Robust Parisian EA for Multidimensional Multiple Sequence Alignment

  • Julie D. Thompson
  • Renaud Vanhoutrève
  • Pierre Collet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10764)

Abstract

This paper describes a new approach for the multiple alignment of biological sequences (DNA or proteins) using a Parisian Evolution approach called MEMSA, for Multidimensional Evolutionary Multiple Sequence Alignment, coded using the EASEA platform. This approach evolves individual sub-alignments called “patches” that are used to create a new kind of Multiple Sequence Alignment where alternative solutions are computed simultaneously using different fitness functions. Solutions are generated by combining coherent sets of high-scoring individuals that are used to reconstruct multi-dimensional multiple sequence alignments. The alignments of this prototype version show a quality comparable to ClustalW (one of the most widely used existing methods) on the 218 samples of the BAliBASE benchmark in reasonable time.

Notes

Acknowledgement

We would like to thank the members of the BISTRO Bioinformatics Platform in Strasbourg for their support. This work was supported by the Agence Nationale de la Recherche (BIPBIP: ANR-10-BINF-03-02), the Région Alsace and Institute funds from the CNRS, the Université de Strasbourg and the Faculté de Médecine de Strasbourg.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.ICube laboratory, UMR CNRS 7357, Strasbourg UniversityStrasbourgFrance
  2. 2.Fédération de Médecine Translationnelle de Strasbourg, CS-DC UNESCO UniTwinStrasbourgFrance

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