Table 3.
Performance of the Contact Map Prediction Methods That Participated in the CASP9 Competition Using Two Performance Metrics (Precision and XD) and Three Confidence Thresholds (L/5, L/10, and Top5)9
| Precision L/5 | Precision L/10 | Precision Top5 | XD L/5 | XD L/10 | XD Top5 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Team ID | Method | Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank |
| RR490 | 3D PSP | 33.8±24.5 | 4.30 (2) | 38.6±28.0 | 4.78 (2) | 46.7±31.7 | 4.59 (2) | 15.1±8.0 | 3.96 (2) | 17.5±8.5 | 3.98 (2) | 19.9±9.4 | 3.96 (2) |
| RR391 | 3D PSP | 32.8±25.0 | 3.74 (1) | 37.2±28.3 | 4.30 (1) | 45.9±33.0 | 3.91 (1) | 15.3±8.4 | 3.28 (1) | 17.3±9.4 | 3.28 (1) | 19.6±10.5 | 3.35 (1) |
| RR051 | Rule-based | 21.1±13.3 | 5.87 (3) | 24.1±16.4 | 5.98 (3) | 25.7±23.2 | 6.11 (4) | 10.6±5.3 | 5.33 (3) | 11.7±7.1 | 5.63 (3) | 11.8±9.0 | 5.96 (3) |
| RR002 | SVM | 21.0±16.0 | 6.15 (4) | 24.3±21.7 | 6.48 (6) | 23.0±25.4 | 7.43 (10) | 10.2±7.4 | 6.07 (4) | 11.6±8.4 | 6.07 (4) | 12.0±9.1 | 6.5 (7) |
| RR138 | Random forest | 20.6±13.9 | 6.24 (5) | 23.3±21.1 | 6.39 (5) | 27.7±24.2 | 6.15 (5) | 10.5±5.3 | 6.33 (5) | 11.5±6.8 | 6.30 (6) | 12.4±7.6 | 6.32 (6) |
| RR103 | Neural network | 20.1±16.2 | 6.35 (6) | 26.9±25.7 | 6.04 (4) | 31.4±34.0 | 5.78 (3) | 9.1±5.6 | 6.96 (7) | 11.1±8.2 | 6.11 (5) | 11.9±10.7 | 6.15 (4) |
| RR375 | Random forest | 19.3±14.5 | 7.09 (8) | 21.9±17.5 | 6.54 (7) | 24.6±21.7 | 6.22 (6) | 10.1±6.0 | 6.46 (6) | 9.9±7.3 | 6.41 (7) | 10.5±8.9 | 6.22 (5) |
| RR244 | Neural network | 18.8±15.0 | 6.41 (7) | 21.5±18.3 | 6.70 (8) | 22.3±23.1 | 7.11 (7) | 9.0±5.8 | 7.39 (9) | 10.0±6.7 | 7.26 (9) | 10.2±8.4 | 7.43 (10) |
| RR422 | Not specified | 16.4±13.7 | 7.61 (9) | 18.3±17.8 | 7.11 (9) | 18.6±19.9 | 7.09 (8) | 7.9±5.2 | 7.30 (8) | 8.6±7.3 | 7.2 (8) | 8.4±7.9 | 7.41 (9) |
| RR119 | Neural network | 15.6±17.3 | 8.13 (11) | 19.0±22.2 | 7.26 (10) | 20.0±24.8 | 7.26 (9) | 7.5±6.9 | 8.13 (10) | 8.6±8.2 | 7.8 (10) | 9.6±8.5 | 7.09 (8) |
| RR080 | Neural network | 14.8±17.4 | 8.30 (12) | 16.7±22.8 | 8.30 (12) | 15.4±25.0 | 8.26 (12) | 7.3±7.2 | 8.39 (11) | 7.7±8.7 | 8.57 (11) | 7.1±9.6 | 8.5 (11) |
| RR214 | Neural network | 14.0±13.2 | 7.80 (10) | 12.1±13.4 | 8.11 (11) | 11.4±16.4 | 8.09 (11) | 6.0±5.7 | 8.41 (12) | 5.0±6.1 | 9.39 (12) | 4.6±7.2 | 9.1 (12) |
Participating teams are identified by their team ID. The row corresponding to our team is marked in bold. For each metric and confidence threshold, we report the average score (higher=better) and average rank of score (lower=better) across the proteins used for test. A brief description of the machine learning method used by each team is provided.