Detection of Covid-19 mutations based on the phyloevolutionary and ORF characterization.
In: AIP Conference Proceedings; 2020, Vol. 2353 Issue 1, p1-6, 6p; Jg. 2353 (2020-10-31) 1, S. 1-6
Konferenz
Zugriff:
The Covid-19 pandemic, which is happening all over the world, needs serious attention. Covid-19 initiated by an RNA type virus can cause more severe problems later on due to its ability to mutate. Integrated molecular research is required to determine the characteristics and potential of various variants of Covid-19 in mutations. This study was conducted by directing phylogenetic analysis on 17 samples of Covid-19 sequences from several countries taken from the NCBI database and followed by ORF analysis of each Covid-19 sample for further characterization. Based on the study, it is known that from 17 samples of Covid-19 sequences, Covid-19 sequences from Taiwan have the lowest similarity compared to 16 other Covid-19 sequences. These results are confirmed by the ORF analysis of each sample, which shows that the longest ORF in the Covid-19 sequence from Taiwan is an ORF 20 with lengthened by 4405 amino acids, and the shortest ORF is an ORF 38 with lengthened by 50 amino acids. However, 16 other sequence samples have the longest ORF 6, ORF 6, with lengthened by 4405 amino acids and the shortest ORF 44 with lengthened by 50 amino acids. The difference in ORF variation affects the similarity level of Covid-19 sequences from several countries. It is due to variations in ORF that produce amino acid variations that determine the Covid-19 phenotype. [ABSTRACT FROM AUTHOR]
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Titel: |
Detection of Covid-19 mutations based on the phyloevolutionary and ORF characterization.
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Autor/in / Beteiligte Person: | Rozana, Kennis ; Susanti, Evi ; Ciptawati, Endang ; Saputra, Indra Kurniawan ; Kurniawan, Dediek Tri ; Fajriyah, Rohmatul ; Taufiq, Ahmad ; Susanto, Hendra ; Nur, Hadi ; Aziz, Muhammad ; Suksuwan, Acharee ; Ng, Chen Siang ; Jemon, Khairunadwa Binti ; Amin, Mohamad ; Diantoro, Markus ; Mufti, Nandang ; Malek, Nik Ahmad Nizam Nik ; Wang, I Ching ; Sunaryono ; Zubaidah, Siti |
Quelle: | AIP Conference Proceedings; 2020, Vol. 2353 Issue 1, p1-6, 6p; Jg. 2353 (2020-10-31) 1, S. 1-6 |
Veröffentlichung: | 2020 |
Medientyp: | Konferenz |
ISSN: | 0094-243X (print) |
DOI: | 10.1063/5.0052908 |
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