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Photonics enabled intelligence system to identify SARS-CoV 2 mutations

delete2022-04-29
delete17
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OA
AI
B
Bakr Ahmed Taha
Q
Qussay Al-Jubouri
Y
Yousif Al Mashhadany
M
Mohd Saiful Dzulkefly Zan
A
Ahmad Ashrif A. Bakar
M
Mahmoud Muhanad Fadhel
N
Norhana Arsad *
DOI:10.1007/s00253-022-11930-1delete
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摘要

摘要

En 中文
The COVID-19, MERS-CoV, and SARS-CoV are hazardous epidemics that have resulted in many deaths which caused a worldwide debate. Despite control efforts, SARS-CoV-2 continues to spread, and the fast spread of this highly infectious illness has posed a grave threat to global health. The effect of the SARS-CoV-2 mutation, on the other hand, has been characterized by worrying variations that modify viral characteristics in response to the changing resistance profile of the human population. The repeated transmission of virus mutation indicates that epidemics are likely to occur. Therefore, an early identification system of ongoing mutations of SARS-CoV-2 will provide essential insights for planning and avoiding future outbreaks. This article discussed the following highlights: First, comparing the omicron mutation with other variants; second, analysis and evaluation of the spread rate of the SARS-CoV 2 variations in the countries; third, identification of mutation areas in spike protein; and fourth, it discussed the photonics approaches enabled with artificial intelligence. Therefore, our goal is to identify the SARS-CoV 2 virus directly without the need for sample preparation or molecular amplification procedures. Furthermore, by connecting through the optical network, the COVID-19 test becomes a component of the Internet of healthcare things to improve precision, service efficiency, and flexibility and provide greater availability for the evaluation of the general population.
Keyword:
SARS-CoV 2
Spike protein
Mutations
COVID-19 variant
Photonic
Intelligence system
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期刊

Applied Microbiology and Biotechnology 封面图
Applied Microbiology and Biotechnology
IF:
4.3
论文数:
1.6W
被引数:
5.4W

机构

University of Technology - Iraq 封面图
University of Technology - Iraq
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1.6K
论文数: 1.6K
被引数: 2.7K
U
Universiti Kebangsaan Malaysia
学者数:
1.5W
论文数: 1.1W
被引数: 126
U
University of Anbar
学者数:
631
论文数: 642
被引数: 828
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