From: Research on RNA secondary structure predicting via bidirectional recurrent neural network
Dataset | Method | SEN | PPV | ACC | MCC |
---|---|---|---|---|---|
SPR | VLDB | 0.962 | 0.885 | 0.921 | 0.845 |
SVM | 0.788 | 0.856 | 0.834 | 0.667 | |
ProbKnot | 0.793 | 0.744 | 0.772 | 0.546 | |
LSTM | 0.703 | 0.71 | 0.687 | 0.372 | |
Cylofold | * | * | * | * | |
ASE | VLDB | 0.826 | 0.652 | 0.727 | 0.475 |
SVM | 0.712 | 0.663 | 0.68 | 0.361 | |
ProbKnot | 0.734 | 0.564 | 0.613 | 0.247 | |
LSTM | 0.81 | 0.739 | 0.574 | 0.786 | |
Cylofold | 0.66 | 0.575 | 0.65 | 0.299 | |
RFA | VLDB | 0.811 | 0.699 | 0.778 | 0.558 |
SVM | 0.151 | 0.748 | 0.581 | 0.182 | |
ProbKnot | 0.793 | 0.555 | 0.648 | 0.339 | |
LSTM | 0.794 | 0.54 | 0.561 | 0.141 | |
Cylofold | 0.667 | 0.551 | 0.584 | 0.177 | |
SRP | VLDB | 0.828 | 0.7 | 0.729 | 0.463 |
SVM | 0.682 | 0.566 | 0.581 | 0.167 | |
ProbKnot | 0.807 | 0.598 | 0.638 | 0.300 | |
LSTM | 0.824 | 0.665 | 0.625 | 0.123 | |
Cylofold | 0.673 | 0.563 | 0.184 | 0.589 | |
TMR | VLDB | 0.796 | 0.669 | 0.765 | 0.529 |
SVM | 0.498 | 0.684 | 0.68 | 0.34 | |
ProbKnot | 0.635 | 0.388 | 0.533 | 0.109 | |
LSTM | 0.85 | 0.538 | 0.569 | 0.18 | |
Cylofold | 0.526 | 0.433 | 0.561 | 0.106 |