Abu Dhabi graduate of Mangaluru Origin helps develop tool to monitor coronavirus mutations

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Abu Dhabi graduate of Mangaluru Origin helps develop tool to monitor coronavirus mutations

Abu Dhabi: A former resident of Abu Dhabi is part of an international research team that has developed a tool to keep track of the mutations of the Covid-19 virus.

Elston Neil D’Souza, the youngest member of the team led by University of Melbourne associate professor David Ascher, helped create the tool called COVID-3D, which harnesses genomic and protein information about the virus.

The changing structures of the virus make it challenging for experts to develop drugs and vaccines; so by monitoring these mutations, COVID-3D becomes an important instrument in the fight against the pandemic.

During the research, D’Souza and his team analysed more than 120,000 samples of the novel coronavirus from infected patients globally. D’Souza, with eight others, co-authored the research paper, which has been peer-reviewed and published in the scientific journal ‘Nature Genetics’.

“With the large amounts of data collected and shared across the world, this pandemic has seen the use of innovative techniques such as genomic sequencing, machine learning and data-sharing. We developed COVID-3D using this vast amount of data,” said D’Souza, an alumnus of Adnoc Schools, Ruwais. He has finished his degree in computational biology at the University of Melbourne and he is now doing another course.

“This tool is an open and freely accessible Web resource that can help researchers around the world.”

D’Souza graduated from Adnoc Schools in 2016 and he attributes a large part of this success to the quality education he received in the Capital. “I am grateful for the many opportunities to learn and grow when I was a science student at Adnoc Schools. I thank the UAE for showing me the importance of working hard with a diverse group of individuals,” the 22-year-old added. His parents are still residing in Ruwais, Abu Dhabi.

ashwani@khaleejtimes.com

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Exploring the structural distribution of genetic variation in SARS-CoV-2 with the COVID-3D online resource


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