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. 2021 Jul 12;37(Suppl 1):i289–i298. doi: 10.1093/bioinformatics/btab288

Table 1.

Evaluation of isoform-level circular RNA prediction based on the 5-fold cross-validation

Method Accuracy Precision Sensitivity Specificity F1-score MCC AUC
SVM 0.7279 ± 0.0686 0.7479 ± 0.0970 0.8932 ± 0.1075 0.4526 ± 0.3413 0.8042 ± 0.0260 0.4031 ± 0.1784 0.6729 ± 0.1203
RF 0.7607 ± 0.0084 0.7764 ± 0.0123 0.8610 ± 0.0077 0.5982 ± 0.0075 0.8165 ± 0.0095 0.4804 ± 0.0115 0.7296 ± 0.0053
Att-CNN 0.7519 ± 0.0069 0.7739 ± 0.0257 0.8529 ± 0.0391 0.5872 ± 0.0527 0.8105 ± 0.0080 0.4612 ± 0.0165 0.7200 ± 0.0097
Att-RNN 0.7638 ± 0.0075 0.7773 ± 0.0161 0.8582 ± 0.0345 0.6171 ± 0.0505 0.8152 ± 0.0094 0.4960 ± 0.0134 0.7377 ± 0.0105
nRC 0.7557 ± 0.0115 0.7844 ± 0.0389 0.8410 ± 0.0597 0.6193 ± 0.0998 0.8094 ± 0.0118 0.4781 ± 0.0279 0.8280 ± 0.0091
PredcircRNA 0.6550 ± 0.0076 0.6977 ± 0.0137 0.5949 ± 0.0070 0.7202 ± 0.0120 0.6422 ± 0.0091 0.3169 ± 0.0164 0.5882 ± 0.0102
circDeep 0.8748 ± 0.0102 0.9393 ± 0.0134 0.8161 ± 0.0217 0.9407 ± 0.0138 0.8732 ± 0.0111 0.7584 ± 0.0186 0.7395 ± 0.0132
DeepCirCode 0.8997 ± 0.0039 0.9353 ± 0.0228 0.9021 ± 0.0248 0.8967 ± 0.0383 0.9179 ± 0.0040 0.7914 ± 0.0073 0.8994 ± 0.0077
JEDI 0.9878 ± 0.0007 0.9906 ± 0.0030 0.9906 ± 0.0032 0.9836 ± 0.0038 0.9904 ± 0.0009 0.9742 ± 0.0014 0.9872 ± 0.0009

Note: We report the mean and standard deviation for each metric.