Research Article
iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network
Table 3
Comparison of the current existing model using 10-fold crossvalidation for classifying TATA and TATA-less promoters.
| Species | Type | Predictor | Sn (%) | Sp (%) | Acc (%) | Mcc |
| Arabidopsis | TATA | iPTT(2 L)-CNN | 95.99 | 97.74 | 97.14 | 0.9366 | CNNProm | 95.00 | 97.00 | 96.11 | 0.91 | TATA-less | iPTT(2 L)-CNN | 94.55 | 96.37 | 95.74 | 0.9065 | CNNProm | 94.00 | 94.00 | 93.77 | 0.8600 | Mouse | TATA | iPTT(2 L)-CNN | 95.52 | 97.68 | 97.08 | 0.9279 | CNNProm | 97.00 | 97.00 | 97.10 | 0.93 | TATA-less | iPTT(2 L)-CNN | 89.11 | 95.94 | 92.91 | 0.8513 | CNNProm | 88.00 | 94.00 | 91.75 | 0.83 |
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