From: DeepQA: improving the estimation of single protein model quality with deep belief networks
QA methods | Corr. on stage 1 /P-Value | Loss on stage 1 /P-Value | Corr. on stage 2 /P-Value | Loss on stage 2 /P-Value |
---|---|---|---|---|
DeepQA | 0.64/- | 0.09/- | 0.42/- | 0.06/- |
ProQ2 | 0.64/4.80E-01 | 0.09/8.32E-01 | 0.37/2.84E-03 | 0.06/9.95E-01 |
Qprob | 0.63/8.08E-01 | 0.10/9.38E-01 | 0.38/8.63E-03 | 0.07/7.12E-01 |
VoroMQA | 0.56/1.60E-04 | 0.11/2.73E-01 | 0.40/2.57E-01 | 0.07/9.14E-01 |
ProQ2-refine | 0.65/6.08E-02 | 0.09/9.17E-01 | 0.37/4.71E-03 | 0.07/4.86E-01 |
Wang_SVM | 0.66/5.49E-02 | 0.11/7.98E-02 | 0.36/1.54E-02 | 0.09/4.91E-02 |
raghavagps-qaspro | 0.35/3.79E-13 | 0.16/1.87E-04 | 0.22/1.92E-10 | 0.09/1.02E-03 |
Wang_deep_2 | 0.63/9.98E-01 | 0.12/7.18E-02 | 0.31/2.16E-06 | 0.09/8.22E-03 |
Wang_deep_1 | 0.61/3.06E-01 | 0.13/1.64E-03 | 0.30/5.93E-06 | 0.09/5.00E-03 |
Wang_deep_3 | 0.63/7.18E-02 | 0.12/3.15E-02 | 0.30/8.22E-03 | 0.09/8.22E-03 |
FUSION | 0.10/8.43E-14 | 0.15/9.78E-04 | 0.05/1.81E-13 | 0.11/2.83E-07 |
RFMQA | 0.54/1.61E-01 | 0.12/8.74E-01 | 0.29/3.80E-03 | 0.08/3.80E-03 |
ProQ3 | 0.65/1.62E-01 | 0.07/3.60E-02 | 0.38/4.44E-01 | 0.06/4.09E-01 |
ResQ* | 0.67/- | 0.05/- | 0.58/- | 0.09/- |
ModFOLDclust2 | 0.74/3.96E-05 | 0.05/6.34E-04 | 0.56/1.80E-03 | 0.07/1.41E-01 |
Mean | 0.57 | 0.11 | 0.33 | 0.08 |