Figure 2

Assessment of CAPPI-Integ predictions. Assessment of CAPPI-Integ predictions. (A) Histogram of BP scores for the fly input datasets (combined) and corresponding inferred datasets of the same size (4049 PPIs in case of Input-3sp and CAPPI-Integ-3sp and 12107 PPIs in case of Input-7sp and CAPPI-Integ). Both CAPPI-Integ and CAPPI-Integ-3sp provide higher-scoring interactomes compared to their input datasets demonstrating the method's ability to use the interactions from distant species to make high quality predictions in other species. (B) Assessment of predicted yeast interactions using the three GO scores. The similarity of GO annotations of each pair of interacting proteins is measured in each ontology: biological process (BP), molecular function (MF) and cellular component (CC). CAPPI and Domain-ML predictions are ranked by their probabilities and the average GO score for the top n predictions is shown. CAPPI-Integ-3sp outperforms the domain based approach trained on the same experimental data. CAPPI-Integ integrates all available data from the seven species and further improves the predictions for yeast. (C) The ratio of true positives (TP) and false positives (FP) as a function of the number of yeast interactions. An interaction is deemed true positive if it is found in the reference dataset comprising co-complex and binary PPIs, and false positive, if the two proteins are assigned different localizations in the MIPS sub-cellular localization catalog (see text). The TP/FP ratios for the CAPPI-Integ, CAPPI-Integ-3sp and Domain-ML predictions are compared with the scores of the input experimental datasets. The gray dashed line marks the level at which the number of true positive predictions is equal to the number of false positive predictions.