Clustering and classification of virus sequence through music communication protocol and wavelet transform.
Genomics
; 113(1 Pt 2): 778-784, 2021 01.
Article
in English
| MEDLINE | ID: covidwho-867194
ABSTRACT
The coronavirus pandemic became a major risk in global public health. The outbreak is caused by SARS-CoV-2, a member of the coronavirus family. Though the images of the virus are familiar to us, in the present study, an attempt is made to hear the coronavirus by translating its protein spike into audio sequences. The musical features such as pitch, timbre, volume and duration are mapped based on the coronavirus protein sequence. Three different viruses Influenza, Ebola and Coronavirus were studied and compared through their auditory virus sequences by implementing Haar wavelet transform. The sonification of the coronavirus benefits in understanding the protein structures by enhancing the hidden features. Further, it makes a clear difference in the representation of coronavirus compared with other viruses, which will help in various research works related to virus sequence. This evolves as a simplified and novel way of representing the conventional computational methods.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Algorithms
/
Genome, Viral
/
Wavelet Analysis
/
SARS-CoV-2
/
COVID-19
/
Music
Type of study:
Prognostic study
Limits:
Humans
Language:
English
Journal:
Genomics
Journal subject:
Genetics
Year:
2021
Document Type:
Article
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