Table 4.
Comparison of secondary structure prediction for three different non-homologous datasets and two different assignment types
DSSP | SKSP+ | ||||||
---|---|---|---|---|---|---|---|
Method | 2640 | 1833 | 1975 | 2640 | 1833 | 1975 | |
SPINE X | Q3 | 82.7±0.5 | 81.3±0.5 | 82.3±0.5 | 83.2±0.4 | 82.1±0.6 | 82.6±0.4 |
QH | 87.4 | 86.1 | 87.4 | 88.1 | 87.1 | 88.0 | |
QE | 74.2 | 72.8 | 74.0 | 72.9 | 71.8 | 72.3 | |
QC | 83.3 | 81.6 | 82.3 | 84.7 | 83.0 | 83.4 | |
| |||||||
PSIPRED | Q3 | 80.9±0.4 | 80.6±0.6 | 81.6±0.4 | 80.6±0.5 | 80.3±0.5 | 80.9±0.4 |
QH | 79.9 | 79.9 | 80.9 | 79.2 | 79.2 | 79.6 | |
QE | 73.2 | 73.1 | 74.3 | 71.8 | 71.4 | 72.3 | |
QC | 86.5 | 85.8 | 86.8 | 86.6 | 87.1 | 87.6 |
Server prediction accuracy for the three different non-homologous datasets described in the text. The SPINE X server was trained on 95% of the 2640 dataset, PSIPRED was trained on its own dataset of 1999 proteins. H denotes Helix, C for Coil, and E for Sheet. Error bars were calculated by splitting all proteins randomly into 10 equally sized sets and calculating the standard deviations of the accuracies among them.