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Chaos game representation dataset of SARS-CoV-2 genome

As of April 16, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 142,000 deaths and more than 2,000,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approac...

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Detalles Bibliográficos
Autores principales: Barbosa, Raquel de M., Fernandes, Marcelo A.C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7182522/
https://www.ncbi.nlm.nih.gov/pubmed/32341946
http://dx.doi.org/10.1016/j.dib.2020.105618
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author Barbosa, Raquel de M.
Fernandes, Marcelo A.C.
author_facet Barbosa, Raquel de M.
Fernandes, Marcelo A.C.
author_sort Barbosa, Raquel de M.
collection PubMed
description As of April 16, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 142,000 deaths and more than 2,000,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approaches such as data stream, digital signal processing, and machine learning techniques and algorithms. However, to make feasible this approach, it is necessary to transform the nucleotide sequences string to numerical values representation. Thus, the dataset provides a chaos game representation (CGR) of SARS-CoV-2 virus nucleotide sequences. The dataset provides the CGR of 100 instances of SARS-CoV-2 virus, 11540 instances of other viruses from the Virus-Host DB dataset, and three instances of Riboviria viruses from NCBI (Betacoronavirus RaTG13, bat-SL-CoVZC45, and bat-SL-CoVZXC21).
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spelling pubmed-71825222020-04-27 Chaos game representation dataset of SARS-CoV-2 genome Barbosa, Raquel de M. Fernandes, Marcelo A.C. Data Brief Biochemistry, Genetics and Molecular Biology As of April 16, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 142,000 deaths and more than 2,000,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approaches such as data stream, digital signal processing, and machine learning techniques and algorithms. However, to make feasible this approach, it is necessary to transform the nucleotide sequences string to numerical values representation. Thus, the dataset provides a chaos game representation (CGR) of SARS-CoV-2 virus nucleotide sequences. The dataset provides the CGR of 100 instances of SARS-CoV-2 virus, 11540 instances of other viruses from the Virus-Host DB dataset, and three instances of Riboviria viruses from NCBI (Betacoronavirus RaTG13, bat-SL-CoVZC45, and bat-SL-CoVZXC21). Elsevier 2020-04-25 /pmc/articles/PMC7182522/ /pubmed/32341946 http://dx.doi.org/10.1016/j.dib.2020.105618 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Biochemistry, Genetics and Molecular Biology
Barbosa, Raquel de M.
Fernandes, Marcelo A.C.
Chaos game representation dataset of SARS-CoV-2 genome
title Chaos game representation dataset of SARS-CoV-2 genome
title_full Chaos game representation dataset of SARS-CoV-2 genome
title_fullStr Chaos game representation dataset of SARS-CoV-2 genome
title_full_unstemmed Chaos game representation dataset of SARS-CoV-2 genome
title_short Chaos game representation dataset of SARS-CoV-2 genome
title_sort chaos game representation dataset of sars-cov-2 genome
topic Biochemistry, Genetics and Molecular Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7182522/
https://www.ncbi.nlm.nih.gov/pubmed/32341946
http://dx.doi.org/10.1016/j.dib.2020.105618
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