Figure 8
From: Improving predicted protein loop structure ranking using a Pareto-optimality consensus method
ROC Curves for Decoys in 1ivd(244:252) and 153 l(98:109). In these ROC curves, the true positives are the number of top-N ranked decoys with RMSD less than or equal to r, the false positives are the number of top-N ranked decoys with RMSD greater than r, the false negatives are the number of decoys with RMSD less than or equal to r but having rank greater than N, and the true negatives are the number of decoys with rank greater than N and RMSD greater than r. In our ROC plots, r is the 10th best RMSD in a decoy set and N is the cutoff variable. The ROC curves generated by the POC method yield higher AUC values than those of the individual scoring functions.