Table 1.

Performance of the individual models according to Matthews Correlation Coefficient (MCC), F1-score, precision and sensitivity on the validation set VL1, and two test sets TS1, TS2 and TS-rfam

Predictor	VL1				TS1				TS2				TS-rfam
	MCC	F1	Precision	Sensitivity	MCC	F1	Precision	Sensitivity	MCC	F1	Precision	Sensitivity	MCC	F1	Precision	Sensitivity
Single Sequence (SS)	0.663	0.713	0.835	0.622	0.671	0.691	0.853	0.581	0.622	0.640	0.812	0.529	0.645	0.664	0.826	0.555
SS + RNAfold (SPOT-RNA-2D-Single)	0.710	0.756	0.863	0.672	0.713	0.733	0.872	0.633	0.713	0.727	0.883	0.618	0.734	0.750	0.890	0.647
SS + PSSM	0.684	0.736	0.830	0.661	0.719	0.748	0.826	0.683	0.670	0.696	0.797	0.618	0.676	0.704	0.797	0.631
SS + DCA (PLMC)	0.681	0.737	0.808	0.677	0.702	0.736	0.779	0.698	0.694	0.720	0.808	0.650	0.681	0.710	0.795	0.642
SS + RNAfold + PSSM + DCA	0.697	0.749	0.828	0.683	0.724	0.752	0.830	0.687	0.714	0.737	0.838	0.657	0.730	0.752	0.851	0.674
SS + RNAfold + PSSM + DCA + MSA Sampling	0.705	0.757	0.827	0.698	0.782	0.806	0.854	0.763	0.713	0.739	0.815	0.675	0.729	0.755	0.829	0.693
SS + RNAfold + PSSM + DCA + MSA Sampling + Ensemble (SPOT-RNA-2D)	0.712	0.760	0.845	0.691	0.800	0.819	0.893	0.757	0.735	0.754	0.870	0.665	0.755	0.773	0.888	0.684

Note: Bold indicates the best performance metric of a model.