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A Novel Coronavirus Genome Identified in a Cluster of Pneumonia Cases - Wuhan, China 2019-2020

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The article was published on 2020-01-01 and is currently open access. It has received 558 citations till now. The article focuses on the topics: Coronavirus.

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Air Emergency Transport under COVID-19: Impact, Measures, and Future

TL;DR: In this paper, the authors make an overall review on the interaction of air transport and the COVID-19 pandemic, and they suggest that air transport should be more digitalized, sustainable, and responsible in the future.
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Safety and immunogenicity evaluation of inactivated whole-virus-SARS-COV-2 as emerging vaccine development in Egypt

TL;DR: In this paper, the authors evaluated the safety and desirable properties of an inactivated SARS-CoV2 vaccine with alum and concluded that the vaccine described here has desirable properties, and their data support further development and plans for clinical trials.
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Artificial Intelligence Technology for COVID-19 Detection at Early Stage with Special Reference to Health Disparity and Socioeconomic Status

Prabir Mandal
TL;DR: Mount Sinai researchers are the first in the country to use artificial intelligence (AI) combined with imaging, and clinical data to analyze patients with COVID-19, a novel coronavirus that has huge potential for analyzing large amounts of data quickly.
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The Great Coronavirus Pandemic of 2019−2021: the Future and the Requirement for China-America Cooperation

TL;DR: The newest and among the most severe pandemic coronavirus disease 2019 (COVID-19) is again caused by an RNA virus, first identified by Chinese medical scientists and shown to be both highly contagious and dangerous.
References
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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

TL;DR: This version of MAFFT has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update.
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A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

TL;DR: This work has used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches.
Journal ArticleDOI

From “A”IV to “Z”IKV: Attacks from Emerging and Re-emerging Pathogens

TL;DR: 100 years after the infamous “Spanish flu” pandemic, the 2017–2018 flu season has been severe, with numerous infections worldwide.
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