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. 2016 Feb 29;6:22286. doi: 10.1038/srep22286

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Copyright © 2016, Macmillan Publishers Limited

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(a) The ROC curves characterizing the potential prediction accuracy of the adhesion and invasion factors of pathogenic Firmicutes and Proteobacteria according to the oligopeptide mass distributions exemplified for 16 different cleavage rules. (b) The ROC curves for the binary logistic regression models representing one to four best linear combinations of predictors using different cleavage rules. The areas under the curves (AUC) are 0.673, 0.813, 0.871 and 0.873, while the Nagelkerke coefficients of determination are 0.164, 0.425, 0.516 and 0.561 for one, two, three and four cleavages used, respectively.

Inline graphic — (a) The ROC curves characterizing the potential prediction accuracy of the adhesion and invasion factors of pathogenic Firmicutes and Proteobacteria according to the oligopeptide mass distributions exemplified for 16 different cleavage rules. (b) The ROC curves for the binary logistic regression models representing one to four best linear combinations of predictors using different cleavage rules. The areas under the curves (AUC) are 0.673, 0.813, 0.871 and 0.873, while the Nagelkerke coefficients of determination are 0.164, 0.425, 0.516 and 0.561 for one, two, three and four cleavages used, respectively.