Figure 6
From: NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction
Posterior trace of Swi5p and Ste5p for our two HMMs. a) Posterior trace of Swi5p, a characterized bipartite cNLS, using our four state model. Output was generated by NLStradamus and highlighted region shows the region of characterized NLS. Black (i) and blue (iii) lines represent the two patches of basic residues while the pink line (ii) represents the spacer. Green line represents the sum of the three NLS states. Red line is shown as a reference for a threshold of 0.6. b) Posterior trace of Swi5p, a characterized bipartite NLS, using our simple two state model. Output was generated by NLStradamus and highlighted region shows the region of characterized NLS. Horizontal red line depicts the chosen posterior threshold of 0.6. c) Posterior trace of Ste5p, a characterized bipartite importin-β dependent NLS (non-cNLS), using our four state model. Output was generated by NLStradamus and highlighted region shows the region of characterized NLS. Black (i) and blue (iii) lines represent the two patches of basic residues while the pink line (ii) represents the spacer. Green line represents the sum of the three NLS states. Red line is shown as a reference for a threshold of 0.6. d) Posterior trace of Ste5p, a characterized bipartite non-classical NLS, using our simple two state model. Output was generated by NLStradamus and highlighted region shows the region of characterized NLS. Horizontal red line depicts the chosen posterior threshold of 0.6.