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A time warping approach to multiple sequence alignment

Authors :
Catherine Matias
Ana Arribas-Gil
Departamento de Estadistica
Universidad Carlos III de Madrid [Madrid] (UC3M)
Laboratoire de Probabilités et Modèles Aléatoires (LPMA)
Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)
Source :
Statistical Applications in Genetics and Molecular Biology, Statistical Applications in Genetics and Molecular Biology, 2017, 16 (2), pp.133-144. ⟨10.1515/sagmb-2016-0043⟩, Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2017, 16 (2), pp.133-144. ⟨10.1515/sagmb-2016-0043⟩
Publication Year :
2017
Publisher :
HAL CCSD, 2017.

Abstract

We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares.

Details

Language :
English
ISSN :
15446115
Database :
OpenAIRE
Journal :
Statistical Applications in Genetics and Molecular Biology, Statistical Applications in Genetics and Molecular Biology, 2017, 16 (2), pp.133-144. ⟨10.1515/sagmb-2016-0043⟩, Statistical Applications in Genetics and Molecular Biology, De Gruyter, 2017, 16 (2), pp.133-144. ⟨10.1515/sagmb-2016-0043⟩
Accession number :
edsair.doi.dedup.....731dfc5c6cf88eac1b93afe7e2645a0d
Full Text :
https://doi.org/10.1515/sagmb-2016-0043⟩