Author: Jakub M Bartoszewicz; Anja Seidel; Bernhard Y Renard
Title: Interpretable detection of novel human viruses from genome sequencing data Document date: 2020_1_30
ID: ac00tai9_44
Snippet: As a proof of concept, we analyze one of the viruses randomly assigned to the test set -the Taï Forest ebolavirus, which has a history of host-switching and can cause a serious disease. To show that the method can also be used for other biological problems, we investigated the networks trained by Bartoszewicz et al. (2019) and their predictions on a genome of a pathogenic bacterium Staphylococcus aureus. The authors used this particular species .....
Document: As a proof of concept, we analyze one of the viruses randomly assigned to the test set -the Taï Forest ebolavirus, which has a history of host-switching and can cause a serious disease. To show that the method can also be used for other biological problems, we investigated the networks trained by Bartoszewicz et al. (2019) and their predictions on a genome of a pathogenic bacterium Staphylococcus aureus. The authors used this particular species to assess the performance of their method on real sequencing data. In this case, we used a stride of 125bp to generate the pseudo-reads. Finally, we analyzed the SARS-CoV-2 coronavirus, which emerged in December 2019, causing a pneumonia outbreak (Wu et al., 2020) .
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