Research Article
CirBiTree: Citrullination Site Inference Based on a Fuzzy Neural Network and Flexible Neural Tree
Table 6
The performances of different methods in length 19.
| Method | Sn (%) | Sp (%) | F1 | MCC |
| DNABIND [34] | 69.64 | 70.86 | 0.7007 | 0.4051 | DNAbinder [34] | 69.75 | 73.56 | 0.7110 | 0.4334 | DBD-Threader [35] | 57.63 | 94.66 | 0.7073 | 0.5630 | DNA-Prot [35] | 67.72 | 80.64 | 0.7240 | 0.4877 | iDNA-Prot [36] | 76.69 | 75.48 | 0.7623 | 0.5218 | DBPPred [37] | 79.32 | 74.79 | 0.7756 | 0.5416 | PLMLA [38] | 65.61 | 69.49 | 0.6691 | 0.3513 | Phosida [39] | 78.58 | 84.77 | 0.8109 | 0.6346 | LysAcet [40] | 77.33 | 75.00 | 0.7644 | 0.5234 | EnsemblePail [41] | 77.20 | 72.20 | 0.7532 | 0.4946 | PSKAcePred [42] | 70.99 | 69.66 | 0.7052 | 0.4065 | BRABSB [43] | 81.07 | 72.12 | 0.7760 | 0.5341 | SSPKA [44] | 75.72 | 79.48 | 0.7717 | 0.5524 | Proposed algorithm | 81.01 | 80.09 | 0.8064 | 0.6111 |
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