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...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
Elsevier BV
2020
|
| Online Access: | https://hdl.handle.net/1721.1/125023 |
| _version_ | 1826192348621570048 |
|---|---|
| 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 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). |
| first_indexed | 2024-09-23T09:10:24Z |
| format | Article |
| id | mit-1721.1/125023 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T09:10:24Z |
| publishDate | 2020 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1250232022-09-30T13:56:28Z Chaos game representation dataset of SARS-CoV-2 genome Barbosa, Raquel de M. Fernandes, Marcelo A.C. Massachusetts Institute of Technology. Department of Chemical Engineering 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). 2020-05-05T18:16:39Z 2020-05-05T18:16:39Z 2020-06 2020-04 Article http://purl.org/eprint/type/JournalArticle 2352-3409 https://hdl.handle.net/1721.1/125023 Barbosa, Raquel de M. and Marcelo A.C.Fernandes. "Chaos game representation dataset of SARS-CoV-2 genome." Data in Brief 30 (June 2020): 105618 © 2020 Elsevier http://dx.doi.org/10.1016/j.dib.2020.105618 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. 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 |
| url | https://hdl.handle.net/1721.1/125023 |
| work_keys_str_mv | AT barbosaraqueldem chaosgamerepresentationdatasetofsarscov2genome AT fernandesmarceloac chaosgamerepresentationdatasetofsarscov2genome |