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Table 4 Note the improvement in prediction accuracy on the supposedly more difficult and longer E. coli RNase P data-set. This shows that MFE methods are less sensitive to folding errors on longer data-sets but are also less likely to resolve the entire structure. There is little difference in algorithm accuracy for each of the methods explored here. Each employs the same energy parameters so differences are due to slightly different implementations.

From: A comprehensive comparison of comparative RNA structure prediction approaches

  E. coli RNase P: Single Sequence Methods
Algorithm number of bps in reference number of bps in prediction True Positives (% sensitivity) False Positives (% selectivity) Correlation (%)
RNAfold 110 116 69 (62.7) 46 (60.0) 0.612 (61.4)
Mfold (1) 110 118 67 (60.9) 49 (57.8) 0.591 (59.3)
Mfold (2) 110 114 67 (60.9) 46 (59.3) 0.599 (60.1)
Mfold (3) 110 118 76 (69.1) 37 (67.3) 0.680 (68.2)
Sfold (1) 110 116 73 (66.4) 42 (63.5) 0.647 (64.9)
Sfold (2) 110 119 86 (78.2) 28 (75.4) 0.767 (76.8)
Sfold (3) 110 117 61 (55.5) 55 (52.6) 0.538 (54.0)