Table 5 Area under the ROC curve performances on the first group of dataset
From: Deep learning architectures for prediction of nucleosome positioning from sequences data
N_score [16] | NuPop [17] | NucEnergEN [14] | Segal [10] | Field [11] | Kaplan [12] | Heijden [13] | Finestr [15] | DLNN-3 | DLNN-5 | |
|---|---|---|---|---|---|---|---|---|---|---|
HM-LC | ∼0.65 | (0.6,0.65) | (0.6,0.65) | (0.35,0.4) | ∼0.65 | ∼0.65 | ∼0.6 | (0.6, 0.65) | 0.79 | 0.81 |
DM-LC | 0.59 | (0.65,0.70) | ∼0.7 | 0.33 | (0.70,0.75) | (0.70,0.75) | (0.65,0.70) | 0.57 | 0.71 | 0.71 |
YS-WG | 0.77 | 0.74 | (0.65,0.70) | 0.49 | 0.77 | ∼0.7 | ∼0.65 | ∼0.7 | 0.79 | 0.83 |
HM-PM | (0.6,0.65) | 0.67 | (0.6,0.65) | (0.4,0.45) | (0.6,0.65) | ∼0.6 | ∼0.55 | ∼0.55 | 0.77 | 0.77 |
DM-PM | 0.62 | ∼0.7 | (0.70,0.75) | 0.32 | (0.70,0.75) | (0.70,0.75) | (0.55,0.6) | (0.5,0.55) | 0.72 | 0.73 |
YS-PM | 0.70 | 0.74 | (0.7,0.75) | 0.52 | 0.79 | (0.7,0.75) | ∼0.65 | ∼0.7 | 0.73 | 0.83 |
HM-5U | (0.55,0.6) | ∼0.65 | ∼0.7 | 0.37 | ∼0.65 | ∼0.65 | ∼0.6 | (0.55,0.6) | 0.67 | 0.68 |
DM-5U | 0.54 | (0.6,0.65) | (0.65,0.70) | 0.38 | (0.65,0.70) | (0.65,0.70) | (0.55,0.6) | ∼0.5 | 0.66 | 0.67 |