Table 4.
Predictors | Rank | GDT-TS | ZScore |
Zhang-Server [31,91,92] | 1 | 2415 | 17.7 |
FOLDpro [37] | 2 | 2389 | 16.6 |
3Dpro [37] | 3 | 2379 | 15.9 |
UNI-EID expm [93] | 4 | 2350 | 13.9 |
CIRCLE [42] | 5 | 2341 | 12.7 |
RAPTOR [94] | 6 | 2328 | 12.6 |
ROBETTA [61,95,96] | 7 | 2328 | 12.1 |
beautshotbase [97] | 8 | 2328 | 11.9 |
FAMS [42] | 9 | 2327 | 12.0 |
FUNCTION [42] | 10 | 2321 | 11.9 |
HHpred1 [39] | 11 | 2314 | 11.2 |
Pcons6 [98] | 12 | 2309 | 11.0 |
Huber-Torda-Srv [99] | 13 | 2306 | 10.8 |
RAPTOR-ACE [100] | 14 | 2300 | 10.7 |
SP3 [63] | 15 | 2295 | 10.4 |
HHpred2 [39] | 16 | 2294 | 10.6 |
SPARKS2 [101] | 17 | 2293 | 10.2 |
HHpred3 [39] | 18 | 2291 | 10.3 |
beautshot [97] | 19 | 2288 | 10.9 |
SP4 [63] | 20 | 2287 | 9.8 |
Column 1 lists the predictor names, column 2 the ranks, column 3 the total GDT-TS scores and column 4 Z-Scores. For a model of each target, Z-score is the normalized GDT-TS score: (x - u)/σ calculated as in [52,90]. Here, x is the GDT-TS score of the model; u is the average GDT-TS score of all predicted models for the target; σ is the standard deviation. For each predictors, the Z-scores for all targets are summed into a total Z-Score to compare them as shown in the table.