Table 4 Everything is the same with table 3 except that the dataset is from Satron's work. Satron's Dataset, Jackknife test:
From: Demonstration of two novel methods for predicting functional siRNA efficiency
| Â | A+B+C | A+B | B+C | A+C | A | B | C |
|---|---|---|---|---|---|---|---|
Cut-off 0.7 | Â | Â | Â | Â | Â | Â | Â |
Accuracy | 78.07% | 74.87% | 75.22% | 78.43% | 76.47% | 74.87% | 74.87% |
Sensitivity | 21.99% | 9.93% | 4.26% | 24.11% | 16.31% | 0.00% | 0.00% |
Specificity | 96.09% | 96.67% | 99.05% | 96.97% | 96.67% | 100.00% | 100.00% |
Pearson | 0.4369 | 0.4458 | 0.4032 | 0.4562 | 0.4432 | 0.2855 | 0.4013 |
ROC | 0.7476 | 0.7488 | 0.7309 | 0.7648 | 0.755 | 0.6554 | 0.7381 |
Cut-off 0.6 | Â | Â | Â | Â | Â | Â | Â |
Accuracy | 71.66% | 68.98% | 73.26% | 73.08% | 70.23% | 68.27% | 70.41% |
Sensitivity | 31.46% | 24.72% | 26.97% | 34.27% | 29.78% | 0.00% | 14.61% |
Specificity | 90.34% | 89.56% | 94.78% | 91.12% | 89.03% | 100.00% | 96.34% |
Pearson | 0.4465 | 0.4327 | 0.4254 | 0.4477 | 0.4533 | 0.3273 | 0.3698 |
ROC | 0.7363 | 0.7228 | 0.7293 | 0.7414 | 0.7375 | 0.6679 | 0.7029 |
Cut-off 0.5 | Â | Â | Â | Â | Â | Â | Â |
Accuracy | 72.55% | 71.12% | 69.34% | 72.19% | 70.77% | 63.99% | 68.09% |
Sensitivity | 58.37% | 54.75% | 47.96% | 56.56% | 55.66% | 40.27% | 34.39% |
Specificity | 81.76% | 81.76% | 83.24% | 82.35% | 80.59% | 79.41% | 90.00% |
Pearson | 0.4868 | 0.4814 | 0.4642 | 0.4976 | 0.4597 | 0.3625 | 0.3994 |
ROC | 0.7706 | 0.7721 | 0.7508 | 0.7846 | 0.755 | 0.685 | 0.7132 |