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Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data
Today, the palindromic analysis of biological sequences, based exclusively on the study of “mirror” symmetry properties, is almost unavoidable. However, other types of symmetry, such as those present in friezes, could allow us to analyze binary sequences from another point of view. New tools, such a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774538/ https://www.ncbi.nlm.nih.gov/pubmed/35052108 http://dx.doi.org/10.3390/e24010082 |
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author | Girault, Jean-Marc Ménigot, Sébastien |
author_facet | Girault, Jean-Marc Ménigot, Sébastien |
author_sort | Girault, Jean-Marc |
collection | PubMed |
description | Today, the palindromic analysis of biological sequences, based exclusively on the study of “mirror” symmetry properties, is almost unavoidable. However, other types of symmetry, such as those present in friezes, could allow us to analyze binary sequences from another point of view. New tools, such as symmetropy and symmentropy, based on new types of palindromes allow us to discriminate binarized [Formula: see text] noise sequences better than Lempel–Ziv complexity. These new palindromes with new types of symmetry also allow for better discrimination of binarized DNA sequences. A relative error of [Formula: see text] of symmetropy is obtained from the HUMHBB and YEAST1 DNA sequences. A factor of 4 between the slopes obtained from the linear fits of the local symmentropies for the two DNA sequences shows the discriminative capacity of the local symmentropy. Moreover, it is highlighted that a certain number of these new palindromes of sizes greater than 30 bits are more discriminating than those of smaller sizes assimilated to those from an independent and identically distributed random variable. |
format | Online Article Text |
id | pubmed-8774538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87745382022-01-21 Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data Girault, Jean-Marc Ménigot, Sébastien Entropy (Basel) Article Today, the palindromic analysis of biological sequences, based exclusively on the study of “mirror” symmetry properties, is almost unavoidable. However, other types of symmetry, such as those present in friezes, could allow us to analyze binary sequences from another point of view. New tools, such as symmetropy and symmentropy, based on new types of palindromes allow us to discriminate binarized [Formula: see text] noise sequences better than Lempel–Ziv complexity. These new palindromes with new types of symmetry also allow for better discrimination of binarized DNA sequences. A relative error of [Formula: see text] of symmetropy is obtained from the HUMHBB and YEAST1 DNA sequences. A factor of 4 between the slopes obtained from the linear fits of the local symmentropies for the two DNA sequences shows the discriminative capacity of the local symmentropy. Moreover, it is highlighted that a certain number of these new palindromes of sizes greater than 30 bits are more discriminating than those of smaller sizes assimilated to those from an independent and identically distributed random variable. MDPI 2022-01-03 /pmc/articles/PMC8774538/ /pubmed/35052108 http://dx.doi.org/10.3390/e24010082 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Girault, Jean-Marc Ménigot, Sébastien Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data |
title | Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data |
title_full | Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data |
title_fullStr | Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data |
title_full_unstemmed | Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data |
title_short | Palindromic Vectors, Symmetropy and Symmentropy as Symmetry Descriptors of Binary Data |
title_sort | palindromic vectors, symmetropy and symmentropy as symmetry descriptors of binary data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774538/ https://www.ncbi.nlm.nih.gov/pubmed/35052108 http://dx.doi.org/10.3390/e24010082 |
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