Figure 2. Evaluation of network inference methods.

Inference methods are indexed according to Table 1. (a) The plots depict the performance for the individual networks (area under precision-recall curve, AUPR) and the overall score summarizing the performance across networks (Methods). R indicates performance of random predictions. C indicates performance of the integrated community predictions. (b) Methods are grouped according to the similarity of their predictions via principal component analysis. Shown are the 2nd vs. 3rd principal components; the 1st principal component accounts mainly for the overall performance (Supplementary Note 4). (c) The heatmap depicts method-specific biases in predicting network motifs. Rows represent individual methods and columns represent different types of regulatory motifs. Red and blue show interactions that are easier and harder to detect, respectively.