Scientists have had a breakthrough in regards to understanding how the genomic signature of the coronavirus works, and how they can classify it.
Computer scientists and biologists used machine learning to identify an underlying genomic signature for 29 different COVID-19 DNA sequences. Why is this important? Because this new data will be able to allow researchers and scientists to quickly identify a deadly virus, such as COVID-19, in just minutes. The speed of identification is paramount in combating the spread of the virus, and according to the researchers, this machine-learning method is 100% accurate.
Biology professor Kathleen Hill co-led the study, and said "All we needed was the COVID-19 DNA sequence to discover its own intrinsic sequence pattern. We used that signature pattern and a logical approach to match that pattern as close as possible to other viruses and achieved a fine level of classification in minutes-not days, not hours but minutes." This new classification tool has already been used to analyze 5,000 unique virus genomic sequences, and Hill believes that the tool will become an essential component for researchers who are creating a vaccine for COVID-19.
It should also be noted that this new machine-learning tool supports the current hypothesis that COVID-19 originated in bats as Sarbecovirus.
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