Author: Alejandro Lopez-Rincon; Alberto Tonda; Lucero Mendoza-Maldonado; Eric Claassen; Johan Garssen; Aletta D. Kraneveld
Title: Accurate Identification of SARS-CoV-2 from Viral Genome Sequences using Deep Learning Document date: 2020_3_14
ID: c2lljdi7_38
Snippet: The query resulted in 407 non-repeated sequences (Table 4) , with 68 sequences 225 belonging to SARS-CoV-2. Then, we applied the whole procedure to translate the data into the sequence feature space, and we run the same state-of-the-art feature selection algorithm [36] . This give us a list of 10 different sequences: just checking for their presence is enough to differentiate between SARS-CoV-2 and other viruses in the dataset with a 100% accurac.....
Document: The query resulted in 407 non-repeated sequences (Table 4) , with 68 sequences 225 belonging to SARS-CoV-2. Then, we applied the whole procedure to translate the data into the sequence feature space, and we run the same state-of-the-art feature selection algorithm [36] . This give us a list of 10 different sequences: just checking for their presence is enough to differentiate between SARS-CoV-2 and other viruses in the dataset with a 100% accuracy. Each of the sequences 230 only appears in SARS-CoV-2. HCoV-OC43 1 105
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