Figure 2. Reliability of LOCtree. The curves show prediction accuracy of LOCtree for eukaryotic animal sequences. (a) Overall performance: the prediction accuracy decreases as we descent the hierarchical tree (Figure 1(a)). The Level 2 accuracy shown includes the accuracy of all Level 1 leaves like the extra-cellular, organelle and nuclear classes (Figure 1(a)), and represents the accuracy of classifying the protein into one of five subcellular classes. At 75% coverage the prediction accuracy is around 94% for Level 0, dropping to 84% for Level 1 and 77% for Level 2. The ability of the hierarchical system to predict intermediate localization states at a significantly higher accuracy is evident from the 17% difference in prediction accuracy between Level 0 and Level 2. Level 1 separates proteins into one of four subcellular classes and is over 7% more accurate than Level 2, which separates proteins into one of five classes. (b) Class-wise performance: LOCtree is best at discriminating secretory pathway proteins from all other proteins (91% accuracy at 50% coverage). Prediction of nuclear and extra-cellular proteins was only slightly less accurate (84% accuracy at 50% coverage) while performance was significantly worse for cytosolic proteins with only 64% correctly predicted. The standard deviation in the prediction accuracy for each of the localization classes was roughly 7%.