ROC analysis: applications to the classification of biological sequences and 3D structures

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easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment (2016, background): “…a signal on the radar screen represented an object or a noise (Egan, 1975; Swets et al., 2000; Fan et al., 2006) and today it is widely used in medicine, radiology, biometrics, bioinformatics and various applications of machine learning and data mining research (Fawcett, 2006; Sonego et al., 2008).”
SMURFLite: combining simplified Markov random fields with simulated evolution improves remote homology detection for beta-structural proteins into the twilight zone (2012, methodology): “We report the area under the curve (AUC statistic) from this ROC curve (Sonego and Pongor, 2008).”
Receiver operating characteristic curve: overview and practical use for clinicians (2022, background): “It has recently also been applied in various other fields, such as bioinformatics and machine learning [7,8].”
pROC: an open-source package for R and S+ to analyze and compare ROC curves (2011, background): “The comparison can be based on AUC [16-19,21], ROC shape [20,22,23], a given specificity [15] or confidence bands [3,24].”