For each of the four centralities (DC, BWC, SC, and GDC) and each of the four categories of BC genes (A, C, HIV, and PI), we find in the human PPI network the top k% of the most central genes (k~1,2,3,:::,100%) and measure how many BC genes they contain. For example, we measure how many cancer genes (C) are in the top 1%, the top 2%, the top 3% etc. most central genes with respect to each of the four centrality measures. We do the same for aging (A), HIV, and PI genes. For a given centrality measure, BC gene category, and k, we quantify the accuracy of the centrality measure in capturing BC genes by computing precision and recall. Precision can be seen as a measure of exactness: it is the percentage of the top k% of the most central genes that are BC genes. Recall can be seen as a measure of completeness: it is the percentage of BC genes of the network that are in the top k% of the most central genes. We need to determine a threshold for k that results in the best combination of precision and recall. Since when varying the values of k, every decrease in precision corresponds to increase in recall, we choose as the threshold for k the point where precision and recall cross ( Figure 5 ). We do this for each of the four centrality measures and each of the four BC gene categories. If the threshold is found to be K, we denote as ''central'' those genes that are amongst the top K% of the most central genes and as ''non-central'' all the remaining genes in the network. We find that the thresholds are 3, 10, 12, and 6, for A, C, HIV, and PI genes, respectively, for each of the four centrality measures.