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Table 5 Comparing the performance of DEEPLYESSENTIAL on down-sampled dataset against methods that solely use sequence features; numbers in boldface indicate the best performance

From: DeeplyEssential: a deep neural network for predicting essential genes in microbes

Method # features AUC Sensitivity PPV
Liu et al. 2017 40 0.794 0.715 0.243
Azhagesan et al. 2018 267 0.838 0.754 0.321
ZUPLS 274 0.705 0.663 0.255
DeeplyEssential 89 0.842 0.801 0.749