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Table 8 Performance comparison with previous studies using newly released data from miRBase.

From: ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors

Tool Positive dataset/negative dataset TP TN FP FN SN SP ACC Balanced ACC MCC
Triplet-SVM   22 88 8 10 68.75% 91.67% 85.94% 80.21% 0.62
MiPred   20 79 17 12 62.50% 82.29% 77.34% 72.40% 0.43
miPred   24 85 11 8 75.00% 88.54% 85.16% 81.77% 0.62
miR-KDE 32/96 23 81 15 9 71.88% 84.38% 81.25% 78.13% 0.53
microPred   23 86 10 9 71.88% 89.58% 85.16% 80.73% 0.61
MiRenSVM   19 81 15 13 59.38% 84.38% 78.13% 71.88% 0.43
miR-BAG   22 82 14 10 68.75% 85.42% 81.25% 77.08% 0.52
ViralmiR   25 85 11 7 78.13% 88.54% 85.94% 83.33% 0.64