Clustering of Zika Viruses Originating from Different Geographical Regions using Computational Sequence Descriptors.
Zika virus
alignment-free
descriptor
clustering
geographical distribution
mahalanobis distance.
principal component analysis
self-organizing map
Journal
Current computer-aided drug design
ISSN: 1875-6697
Titre abrégé: Curr Comput Aided Drug Des
Pays: United Arab Emirates
ID NLM: 101265750
Informations de publication
Date de publication:
2021
2021
Historique:
received:
02
10
2019
revised:
18
11
2019
accepted:
09
12
2019
pubmed:
28
12
2019
medline:
15
12
2021
entrez:
28
12
2019
Statut:
ppublish
Résumé
In this report, we consider a data set, which consists of 310 Zika virus genome sequences taken from different continents, Africa, Asia and South America. The sequences, which were compiled from GenBank, were derived from the host cells of different mammalian species (Simiiformes, Aedes opok, Aedes africanus, Aedes luteocephalus, Aedes dalzieli, Aedes aegypti, and Homo sapiens). For chemometrical treatment, the sequences have been represented by sequence descriptors derived from their graphs or neighborhood matrices. The set was analyzed with three chemometrical methods: Mahalanobis distances, principal component analysis (PCA) and self organizing maps (SOM). A good separation of samples with respect to the region of origin was observed using these three methods. Study of 310 Zika virus genome sequences from different continents. To characterize and compare Zika virus sequences from around the world using alignment-free sequence comparison and chemometrical methods. Mahalanobis distance analysis, self organizing maps, principal components were used to carry out the chemometrical analyses of the Zika sequence data. Genome sequences are clustered with respect to the region of origin (continent, country). Africa samples are well separated from Asian and South American ones.
Sections du résumé
BACKGROUND
BACKGROUND
In this report, we consider a data set, which consists of 310 Zika virus genome sequences taken from different continents, Africa, Asia and South America. The sequences, which were compiled from GenBank, were derived from the host cells of different mammalian species (Simiiformes, Aedes opok, Aedes africanus, Aedes luteocephalus, Aedes dalzieli, Aedes aegypti, and Homo sapiens).
METHODS
METHODS
For chemometrical treatment, the sequences have been represented by sequence descriptors derived from their graphs or neighborhood matrices. The set was analyzed with three chemometrical methods: Mahalanobis distances, principal component analysis (PCA) and self organizing maps (SOM). A good separation of samples with respect to the region of origin was observed using these three methods.
RESULTS
RESULTS
Study of 310 Zika virus genome sequences from different continents. To characterize and compare Zika virus sequences from around the world using alignment-free sequence comparison and chemometrical methods.
CONCLUSION
CONCLUSIONS
Mahalanobis distance analysis, self organizing maps, principal components were used to carry out the chemometrical analyses of the Zika sequence data. Genome sequences are clustered with respect to the region of origin (continent, country). Africa samples are well separated from Asian and South American ones.
Identifiants
pubmed: 31878862
pii: CAD-EPUB-103225
doi: 10.2174/1573409916666191226110936
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
314-322Informations de copyright
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