On DNA numerical representations for genomic similarity computation

Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear...

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Autores principales: Mendizabal-Ruiz, Gerardo, Román-Godínez, Israel, Torres-Ramos, Sulema, Salido-Ruiz, Ricardo A., Morales, J. Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5360225/
https://www.ncbi.nlm.nih.gov/pubmed/28323839
http://dx.doi.org/10.1371/journal.pone.0173288
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author Mendizabal-Ruiz, Gerardo
Román-Godínez, Israel
Torres-Ramos, Sulema
Salido-Ruiz, Ricardo A.
Morales, J. Alejandro
author_facet Mendizabal-Ruiz, Gerardo
Román-Godínez, Israel
Torres-Ramos, Sulema
Salido-Ruiz, Ricardo A.
Morales, J. Alejandro
author_sort Mendizabal-Ruiz, Gerardo
collection PubMed
description Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when using a signal processing technique to analyze them. In this paper, we present an experimental study of the characteristics of nine of the most frequently-used DNR. The objective of this paper is to evaluate the behavior of each representation when used to measure the similarity of a given pair of DNA sequences.
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spelling pubmed-53602252017-04-06 On DNA numerical representations for genomic similarity computation Mendizabal-Ruiz, Gerardo Román-Godínez, Israel Torres-Ramos, Sulema Salido-Ruiz, Ricardo A. Morales, J. Alejandro PLoS One Research Article Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when using a signal processing technique to analyze them. In this paper, we present an experimental study of the characteristics of nine of the most frequently-used DNR. The objective of this paper is to evaluate the behavior of each representation when used to measure the similarity of a given pair of DNA sequences. Public Library of Science 2017-03-21 /pmc/articles/PMC5360225/ /pubmed/28323839 http://dx.doi.org/10.1371/journal.pone.0173288 Text en © 2017 Mendizabal-Ruiz et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mendizabal-Ruiz, Gerardo
Román-Godínez, Israel
Torres-Ramos, Sulema
Salido-Ruiz, Ricardo A.
Morales, J. Alejandro
On DNA numerical representations for genomic similarity computation
title On DNA numerical representations for genomic similarity computation
title_full On DNA numerical representations for genomic similarity computation
title_fullStr On DNA numerical representations for genomic similarity computation
title_full_unstemmed On DNA numerical representations for genomic similarity computation
title_short On DNA numerical representations for genomic similarity computation
title_sort on dna numerical representations for genomic similarity computation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5360225/
https://www.ncbi.nlm.nih.gov/pubmed/28323839
http://dx.doi.org/10.1371/journal.pone.0173288
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