Skip to main content

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)