Research Article
Rule-Based Knowledge Acquisition Method for Promoter Prediction in Human and Drosophila Species
Table 7
The rule-based knowledge of promoter prediction in human and Drosophila species.
| Species | Rule-based knowledge | | | CF | Rules | Accuracy |
| (Human) | | | | | | | R1-p: | If (A, 1st) > 0.0177542 | Then | Promoter | 0.928 | 1 | 50.0% | R2-n: | If (A, 1st) 0.0177542 | Then | Non-promoter | 0.999 | 1-2 | 96.2% | R3-n: | If > 0.284657 and (A, 1st) 0.0950018 and (C, 100%) 0.929016 | Then | Non-promoter | 0.985 | 1–3 | 99.5% | R4-n: | If (GCTC) > 0.0634629 and > 0.284657 and (A, 1st) 0.0950018 | Then | Non-promoter | 0.974 | | | (Drosophila) | | | | | | | R1-p: | If 0.280113 and > 0.27604 | Then | Promoter | 0.997 | 1 | 50.0% | R2-n: | If 0.27604 | Then | Non-promoter | 0.999 | 1-2 | 84.7% | R3-n: | If > 0.280113 | Then | Non-promoter | 0.997 | | |
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