id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-287658-c2lljdi7	Lopez-Rincon, Alejandro	Classification and Specific Primer Design for Accurate Detection of SARS-CoV-2 Using Deep Learning	2020-09-10		.txt	text/plain	4766	253	55	The discovered sequences are first validated on samples from other repositories, and proven able to separate SARS-CoV-2 from different virus strains with near-perfect accuracy. The discovered sequences are validated on samples from NCBI and GISAID, and proven able to separate SARS-CoV-2 from different virus strains with near-perfect accuracy. For example, we can use this sequencing data with cDNA, resulting from the PCR of the original viral RNA; e,g, Real-Time PCR amplicons to identify the SARS-CoV-2 16 . The global impact of SARS-CoV-2 prompted researchers to apply effective alignment-free methods to the classification of the virus: For example, in 26 the authors propose the use of Machine Learning Digital Signal Processing for separating the virus from similar strains, with remarkable accuracy. We calculated the frequency of appearance of different primer sets' sequences used in SARS-CoV-2 RT-PCR tests developed by WHO referral laboratories and compared it to our primer design in the dataset from the GISAID ( Table 2) repository.	./cache/cord-287658-c2lljdi7.txt	./txt/cord-287658-c2lljdi7.txt