Table 1.

Prediction accuracy for various prediction algorithms

	Mean (CI) S-STRAND2 F-measure	Mean testset F-measure	Mean testset 2 F-measure	Citation
AveRNA	0.716 (0.707, 0.725)	0.711 (0.701, 0.721)	0.725 (0.713, 0.737)	-
BL-FR*	0.703 (0.694, 0.712)	0.698 (0.687, 0.708)	0.717 (0.706, 0.729)	[5]
BL*	0.688 (0.678, 0.698)	0.686 (0.675, 0.696)	0.704 (0.692, 0.715)	[5]
CG*	0.676 (0.666, 0.685)	0.673 (0.662, 0.684)	0.690 (0.677, 0.702)	[4]
DIM-CG	0.668 (0.658, 0.678)	0.664 (0.654, 0.674)	0.681 (0.668, 0.695)	[5]
NOM-CG	0.656 (0.646, 0.667)	0.653 (0.643, 0.663)	0.667 (0.655, 0.680)	[5]
CONTRAfold2.0	0.656 (0.647, 0.665)	0.650 (0.640, 0.660)	0.657 (0.644, 0.668)	[3]
CentroidFold	0.643 (0.633, 0.652)	0.638 (0.627, 0.648)	0.643 (0.630, 0.655)	[7]
MaxExpect	0.625 (0.615, 0.635)	0.619 (0.607, 0.630)	0.633 (0.620, 0.646)	[6]
CONTRAfold1.1	0.601 (0.591, 0.610)	0.595 (0.584, 0.605)	0.605 (0.592, 0.619)	[3]
T99	0.597 (0.587, 0.607)	0.591 (0.581, 0.602)	0.606 (0.593, 0.619)	[1]

F measures and 95% confidence intervals, calculated using bootstrapping, and shown in parentheses.