Table 5 Results of BayesMotif with or without false positive removal on real datasets
From: BayesMotif: de novo protein sorting motif discovery from impure datasets
| Â | True motif Ratio | 10% | 20% | 40% | 50% | 80% | 100% |
|---|---|---|---|---|---|---|---|
Without False Positive Removal | Found by Algorithm | No | No | No | Yes | Yes | Yes |
|  | Motif Score |  |  |  | 0.55 ± 0.03 | 0.77 ± 0.01 | 0.91 ± 0.02 |
|  | Motif Information |  |  |  | 19.0 ± 3.24 | 31.6 ± 0.5 | 39.5 ± 0.20 |
With False Positive Removal | Found by Algorithm | No | Yes | Yes | Yes | Yes | Yes |
|  | Motif Score |  | 0.63 ± 0.11 | 0.82 ± 0.04 | 0.83 ± 0.04 | 0.90 ± 0.02 | 0.92 ± 0.01 |
|  | Motif Information |  | 21.5 ± 1.3 | 36.4 ± 2.4 | 38.0 ± 2.4 | 41.2 ± 1.1 | 42.0 ± 0.49 |