Table 3.
Prediction settings and results for the nine gene functions.
Terminase | Portal | Head | Tail | Tape measure | Prohead protease | Lysin | Holin | Integrase | |
# positive samples | 93 | 83 | 26 | 26 | 21 | 11 | 25 | 69 | 67 |
# negative samples | 308 | 195 | 107 | 133 | 82 | 28 | 45 | 213 | 102 |
# clusters | 17 | 15 | 7 | 6 | 7 | 4 | 6 | 16 | 12 |
Prediction Accuracy at t = 0.1(%) | 86.9 | 85.89 | 67.87 | 83.33 | 75.68 | 66.67 | 100 | 79.5 | 82.18 |
The total number (#) of positive training samples, negative training samples and the number of clusters involved with each gene class are shown. Accuracy values are computed using leave-one-out cross validations. K-Means adaptive threshold t = 0.1. GRBF kernel's σ = 2 for Head and Tail; σ = 11.3 for all other cases.