Selected article for: "human blood virome DATASET and virome DATASET"
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_50
    Snippet: We benchmarked our models against the human blood virome dataset used by Zhang et al. (2019) . Our models outperform their k-NN classifier. As the positive class massively outnumbers the negative class, all models achieve over 99% precision. CNN All-150 performs best (Table. 4 ). However, the positive class is dominated by viruses which are not necessarily novel. The CNN was more accurate on training data, so we expected it to detect those viruse.....
    Document: We benchmarked our models against the human blood virome dataset used by Zhang et al. (2019) . Our models outperform their k-NN classifier. As the positive class massively outnumbers the negative class, all models achieve over 99% precision. CNN All-150 performs best (Table. 4 ). However, the positive class is dominated by viruses which are not necessarily novel. The CNN was more accurate on training data, so we expected it to detect those viruses easily.

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