Figure 7
From: Feature-based multiple models improve classification of mutation-induced stability changes
ROC curves performance of EASE-MM, our previous work, and three currently available methods. The true positive rate is shown as a function of the false positive rate at different prediction thresholds. These are independent test results with the S238 data set. EASE-MM, EASE-AA, I-Mutant2.0, MuStab, and MUpro achieved the area under the ROC curve (AUC) of 0.85, 0.83, 0.70, 0.67 and 0.65, respectively.