Data stream dataset of SARS-CoV-2 genome

As of May 25, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 348,000 deaths and more than 5,550,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approache...

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Main Authors: Barbosa, Raquel de M., Fernandes, Marcelo A.C.
Other Authors: Massachusetts Institute of Technology. Department of Chemical Engineering
Format: Article
Published: Elsevier BV 2020
Online Access:https://hdl.handle.net/1721.1/126305
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author Barbosa, Raquel de M.
Fernandes, Marcelo A.C.
author2 Massachusetts Institute of Technology. Department of Chemical Engineering
author_facet Massachusetts Institute of Technology. Department of Chemical Engineering
Barbosa, Raquel de M.
Fernandes, Marcelo A.C.
author_sort Barbosa, Raquel de M.
collection MIT
description As of May 25, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 348,000 deaths and more than 5,550,000 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 techniques and algorithms. However, to make feasible this approach, it is necessary to transform the nucleotide sequences string to numerical stream representation. Thus, the dataset provides four kinds of data stream representation (DSR) of SARS-CoV-2 virus nucleotide sequences. The dataset provides the DSR of 1557 instances of SARS-CoV-2 virus, 11540 other 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 mit-1721.1/1263052022-09-29T22:23:05Z Data stream dataset of SARS-CoV-2 genome Barbosa, Raquel de M. Fernandes, Marcelo A.C. Massachusetts Institute of Technology. Department of Chemical Engineering As of May 25, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 348,000 deaths and more than 5,550,000 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 techniques and algorithms. However, to make feasible this approach, it is necessary to transform the nucleotide sequences string to numerical stream representation. Thus, the dataset provides four kinds of data stream representation (DSR) of SARS-CoV-2 virus nucleotide sequences. The dataset provides the DSR of 1557 instances of SARS-CoV-2 virus, 11540 other 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). 2020-07-22T13:53:24Z 2020-07-22T13:53:24Z 2020-08 2020-06 Article http://purl.org/eprint/type/JournalArticle 2352-3409 https://hdl.handle.net/1721.1/126305 Barbosa, Raquel de M. and Marcelo A.C. Fernandes. "Data stream dataset of SARS-CoV-2 genome." Data in Brief 31 (August 2020): 105829 © 2020 The Author(s) http://dx.doi.org/10.1016/j.dib.2020.105829 Data in Brief Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Elsevier BV Elsevier
spellingShingle Barbosa, Raquel de M.
Fernandes, Marcelo A.C.
Data stream dataset of SARS-CoV-2 genome
title Data stream dataset of SARS-CoV-2 genome
title_full Data stream dataset of SARS-CoV-2 genome
title_fullStr Data stream dataset of SARS-CoV-2 genome
title_full_unstemmed Data stream dataset of SARS-CoV-2 genome
title_short Data stream dataset of SARS-CoV-2 genome
title_sort data stream dataset of sars cov 2 genome
url https://hdl.handle.net/1721.1/126305
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