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Geometric construction of viral genome space and its applications

Understanding the relationships between genomic sequences is essential to the classification and characterization of living beings. The classes and characteristics of an organism can be identified in the corresponding genome space. In the genome space, the natural metric is important to describe the...

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Detalles Bibliográficos
Autores principales: Sun, Nan, Pei, Shaojun, He, Lily, Yin, Changchuan, He, Rong Lucy, Yau, Stephen S.-T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353408/
https://www.ncbi.nlm.nih.gov/pubmed/34429843
http://dx.doi.org/10.1016/j.csbj.2021.07.028
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author Sun, Nan
Pei, Shaojun
He, Lily
Yin, Changchuan
He, Rong Lucy
Yau, Stephen S.-T.
author_facet Sun, Nan
Pei, Shaojun
He, Lily
Yin, Changchuan
He, Rong Lucy
Yau, Stephen S.-T.
author_sort Sun, Nan
collection PubMed
description Understanding the relationships between genomic sequences is essential to the classification and characterization of living beings. The classes and characteristics of an organism can be identified in the corresponding genome space. In the genome space, the natural metric is important to describe the distribution of genomes. Therefore, the similarity of two biological sequences can be measured. Here, we report that all of the viral genomes are in 32-dimensional Euclidean space, in which the natural metric is the weighted summation of Euclidean distance of k-mer natural vectors. The classification of viral genomes in the constructed genome space further proves the convex hull principle of taxonomy, which states that convex hulls of different families are mutually disjoint. This study provides a novel geometric perspective to describe the genome sequences.
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spelling pubmed-83534082021-08-23 Geometric construction of viral genome space and its applications Sun, Nan Pei, Shaojun He, Lily Yin, Changchuan He, Rong Lucy Yau, Stephen S.-T. Comput Struct Biotechnol J Research Article Understanding the relationships between genomic sequences is essential to the classification and characterization of living beings. The classes and characteristics of an organism can be identified in the corresponding genome space. In the genome space, the natural metric is important to describe the distribution of genomes. Therefore, the similarity of two biological sequences can be measured. Here, we report that all of the viral genomes are in 32-dimensional Euclidean space, in which the natural metric is the weighted summation of Euclidean distance of k-mer natural vectors. The classification of viral genomes in the constructed genome space further proves the convex hull principle of taxonomy, which states that convex hulls of different families are mutually disjoint. This study provides a novel geometric perspective to describe the genome sequences. Research Network of Computational and Structural Biotechnology 2021-07-27 /pmc/articles/PMC8353408/ /pubmed/34429843 http://dx.doi.org/10.1016/j.csbj.2021.07.028 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Sun, Nan
Pei, Shaojun
He, Lily
Yin, Changchuan
He, Rong Lucy
Yau, Stephen S.-T.
Geometric construction of viral genome space and its applications
title Geometric construction of viral genome space and its applications
title_full Geometric construction of viral genome space and its applications
title_fullStr Geometric construction of viral genome space and its applications
title_full_unstemmed Geometric construction of viral genome space and its applications
title_short Geometric construction of viral genome space and its applications
title_sort geometric construction of viral genome space and its applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353408/
https://www.ncbi.nlm.nih.gov/pubmed/34429843
http://dx.doi.org/10.1016/j.csbj.2021.07.028
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