University of Waterloo biology professor Kathleen Hill co-led a team of researchers whove identified an underlying genomic signature for 29 different COVID-19 sequences. They did this using a new graphics-based software classification tool powered by machine learning. When sequencing the genome of a virus like COVID-19, the classification software makes use of a decision tree method to run through the best possible choices and achieve a 100 percent accurate outcome within minutes.<\/p>\n
This is a 3D map of researchers' machine learning classification tool. (a) 3,273 viral sequences from the researchers first test, representing 11 viral families and realm Riboviria; (b) 2,779 viral sequences from the second test, classifying 12 viral families of realm Riboviria; and (c) 208 Coronaviridae sequences classified into genera. (Image courtesy of PLOS.)<\/p>\n
Researchers wrote a paper about their findings called Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study. According to the paper, The proposed method combines supervised machine learning with digital signal processing (MLDSP) for genome analyses, augmented by a decision tree approach to the machine learning component, and a Spearmans rank correlation coefficient analysis for result validation. These tools are used to analyze a large dataset of over 5000 unique viral genomic sequences, totaling 61.8 million bp, including the 29 COVID-19 virus sequences available on January 27, 2020.<\/p>\n
The teams results confirm the currently accepted hypothesis that COVID-19 (SARS-CoV-2) originated from bats, and their results classified it as Sarbecovirus within Betacoronavirus. The findings suggest that their machine learning approach is a reliable, scalable and quick option for taxonomic classification of novel viruses. This means that the tool can be used to better serve real-time worldwide reaction and strategy to combat novel viruses in the future.<\/p>\n
Mobilizing medical personnel to react as quickly as possible is invaluable in the fight against a global pandemic and will also be incredibly useful in helping develop correct treatments to outbreaks of novel viruses, including the rapid development of vaccines.<\/p>\n
Bottom Line<\/p>\n
The research is encouraging for future outbreaks, but what it means for the treatment and rapid development of vaccines for the COVID-19 outbreak remains unclear. New studies are showing the efficacy of Remdesivir in treating patients infected with COVID-19, and two vaccinations from Oxford and Germany that seem to be making rapid progress are set to begin human trials in the coming months. Lets hope for the best.<\/p>\n
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