Publicação
Computational analysis of the SARS-CoV-2 and other viruses based on the Kolmogorov’s complexity and Shannon’s information theories
| dc.contributor.author | Machado, J. A. Tenreiro | |
| dc.contributor.author | Rocha-Neves, João M. | |
| dc.contributor.author | Andrade, José P. | |
| dc.date.accessioned | 2022-01-12T11:06:08Z | |
| dc.date.available | 2022-01-12T11:06:08Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | This paper tackles the information of 133 RNA viruses available in public databases under the light of several mathematical and computational tools. First, the formal concepts of distance metrics, Kolmogorov complexity and Shannon information are recalled. Second, the computational tools available presently for tackling and visualizing patterns embedded in datasets, such as the hierarchical clustering and the multidimensional scaling, are discussed. The synergies of the common application of the mathematical and computational resources are then used for exploring the RNA data, cross-evaluating the normalized compression distance, entropy and Jensen–Shannon divergence, versus representations in two and three dimensions. The results of these different perspectives give extra light in what concerns the relations between the distinct RNA viruses. | pt_PT |
| dc.description.sponsorship | The authors thank all those who have contributed and shared sequences to the GISAID database (https://www.gisaid.org/). The authors also thank those who have contributed to the GenBank of the National Center for Biotechnology Information (NCBI) databases (https://www.ncbi.nlm.nih.gov/genbank). The authors also thank Rómulo Antão for the help in handling the information with the compressors zlib and bz2. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1007/s11071-020-05771-8 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/19414 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Springer | pt_PT |
| dc.relation.publisherversion | https://link.springer.com/article/10.1007/s11071-020-05771-8 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | COVID-19 | pt_PT |
| dc.subject | Kolmogorov complexity theory | pt_PT |
| dc.subject | Shannon information theory | pt_PT |
| dc.subject | Hierarchical clustering | pt_PT |
| dc.subject | Multidimensional scaling | pt_PT |
| dc.title | Computational analysis of the SARS-CoV-2 and other viruses based on the Kolmogorov’s complexity and Shannon’s information theories | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 1750 | pt_PT |
| oaire.citation.issue | 3 | pt_PT |
| oaire.citation.startPage | 1731 | pt_PT |
| oaire.citation.title | Nonlinear Dynamics | pt_PT |
| oaire.citation.volume | 101 | pt_PT |
| person.familyName | Tenreiro Machado | |
| person.givenName | J. A. | |
| person.identifier.ciencia-id | 7A18-4935-5B29 | |
| person.identifier.orcid | 0000-0003-4274-4879 | |
| person.identifier.rid | M-2173-2013 | |
| person.identifier.scopus-author-id | 55989030100 | |
| rcaap.rights | closedAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 82cd5c17-07b6-492b-b3e3-ecebdad1254f | |
| relation.isAuthorOfPublication.latestForDiscovery | 82cd5c17-07b6-492b-b3e3-ecebdad1254f |