Unraveling Protein Networks with Power Graph Analysis
Figure 11
Robustness of Power Graph Analysis through Random Rewiring.
Noise level is defined as the number of edges different from the original networks. Random rewiring leaves the total number of edges unchanged, thus a noise level of 100% means that all edges have changed. (A) Comparison of the power node hierarchies. The F1-measure of the precision and recall is computed between the power nodes found for the original network, and power nodes found for the rewired networks. (B) Comparison of the proximity of nodes in the power node hierarchies. Recall is obtained by comparing pairs of nodes together in a power node with the corresponding pairs of nodes in the power graph after random rewiring, the more distant in the power node hierarchy the lower the recall. Precision is obtained by starting from pairs of nodes together in power nodes found in the rewired networks and looking how far–in the power node hierarchy–are the corresponding nodes in the original network. The F1-measure of precision and recall is reported.