Table 4.
The complementary usage of different methods can lead to an improved performance in identifying important pairs in sequences
| Sensitivity | Specificity | MCC | |
|---|---|---|---|
| PC-TraFF20∪MC | 2.8 % | 99.5 % | 0.101 |
| PC-TraFF50∪MC | 3.6 % | 99.3 % | 0.112 |
| PC-TraFF100∪MC | 3.8 % | 99.3 % | 0.114 |
| PC-TraFF20∪CPM | 2.6 % | 99.5 % | 0.099 |
| PC-TraFF50∪CPM | 3.4 % | 99.3 % | 0.107 |
| PC-TraFF100∪CPM | 3.5 % | 99.3 % | 0.109 |
| PC-TraFF20∪CrmM | 3.0 % | 99.2 % | 0.087 |
| PC-TraFF50∪CrmM | 3.8 % | 99 % | 0.10 |
| PC-TraFF100∪CrmM | 3.9 % | 99 % | 0.102 |
| MC ∪CPM | 1.0 % | 99.9 % | 0.079 |
| MC ∪CrmM | 1.2 % | 99.6 % | 0.050 |
| CPM ∪CrmM | 1.2 % | 99.6 % | 0.051 |
| PC-TraFF20∪MC ∪CPM | 3.1 % | 99.5 % | 0.11 |
| PC-TraFF50∪MC ∪CPM | 3.8 % | 99.3 % | 0.118 |
| PC-TraFF100∪MC ∪CPM | 4 % | 99.3 % | 0.12 |
| PC-TraFF20∪MC ∪CPM ∪CrmM | 3.8 % | 99.2 % | 0.10 |
| PC-TraFF50∪MC ∪CPM ∪CrmM | 4.5 % | 99 % | 0.116 |
| PC-TraFF100∪MC ∪CPM ∪CrmM | 4.7 % | 99 % | 0.119 |
| MC ∪CPM ∪CrmM | 1.7 % | 99.6 % | 0.07 |