Research Article
CirBiTree: Citrullination Site Inference Based on a Fuzzy Neural Network and Flexible Neural Tree
Table 8
The performances of different methods in length 21.
| Method | Sn (%) | Sp (%) | F1 | MCC |
| DNABIND [34] | 71.87 | 71.78 | 0.7184 | 0.4365 | DNAbinder [34] | 70.97 | 74.70 | 0.7232 | 0.4571 | DBD-Threader [35] | 58.87 | 95.52 | 0.7208 | 0.5846 | DNA-Prot [35] | 68.56 | 81.27 | 0.7321 | 0.5024 | iDNA-Prot [36] | 78.70 | 76.20 | 0.7773 | 0.5492 | DBPPred [37] | 80.19 | 75.19 | 0.7823 | 0.5545 | PLMLA [38] | 66.05 | 70.64 | 0.6760 | 0.3673 | Phosida [39] | 80.33 | 85.15 | 0.8231 | 0.6556 | LysAcet [40] | 78.36 | 76.00 | 0.7745 | 0.5437 | EnsemblePail [41] | 77.84 | 72.47 | 0.7581 | 0.5039 | PSKAcePred [42] | 72.09 | 70.33 | 0.7146 | 0.4243 | BRABSB [43] | 81.30 | 73.06 | 0.7809 | 0.5455 | SSPKA [44] | 76.10 | 80.55 | 0.7783 | 0.5670 | Proposed algorithm | 83.07 | 80.50 | 0.8201 | 0.6359 |
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