Figure 7
From: NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction
True positive and false positive rate of our model on other species. True positive and false positive rate of various methods, including our HMM at various posterior threshold and the Viterbi algorithm on the PredictNLS dataset. This ROC curve was created by counting overlaps. The false positive rate is shown as the error rate per amino acid residue. The diagonal line depicts a ratio of one true prediction per false prediction per amino acid residue.