Survey
* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
B A Number of complexes Functional homogentity in PI complexes 3.5 P < 0.001 3 2.5 2 100 R = 0.878 10 1 0.1 2 1 10 100 Number of subunits 1.5 C 1 Distribution of node connectivity 1000 Integrated PI score >= 0.7 0.5 Number of nodes Cluster cohesiveness (Z-score) Distribution of complex size 1000 optimal MCL inflation Integrated PI score >= 0.75 mcl1.2 mcl2 mcl3 mcl4 mcl5 mcl1.2 mcl2 mcl2.1 mcl3 mcl4 mcl5 mcl1.2 mcl2 mcl3 mcl4 mcl5 mcl1.2 mcl2 mcl3 mcl4 mcl5 mcl1.2 mcl2 mcl3 mcl4 mcl5 mcl1.2 mcl2 mcl3 mcl4 mcl5 mcl1.2 mcl2 mcl3 mcl4 mcl5 0 0 hubs 10 hubs 20 hubs 30 hubs 50 hubs 100 hubs 100 2 R = 0.906 10 1 200 hubs 0.1 0.1 1 10 100 Number of edges E D 1000 Number of modules 40 35 30 P << 0.001 25 20 100 R 2 = 0.783 10 1 0.1 1 15 10 100 Number of subunits F 10 Distribution of node connectivity Integrated GC score >= 0.75 5 optimal MCL inflation Integrated GC score >= 0.8 1000 0 hubs 10 hubs 100 hubs mcl5 mcl4 mcl3 mcl2 mcl1.2 mcl5 mcl4 mcl3 mcl2 mcl1.2 mcl5 mcl4 mcl3 mcl2 mcl1.7 mcl1.2 0 Number of nodes Cluster cohesiveness (Z-score) Distribution of module size Functional homogentity in GC modules R 2 = 0.783 100 10 1 0.1 0.1 1 10 100 100 Number of edges Figure S2 – Functional homogeneity, connectivity and cluster size in PI complexes and GC modules. Three parameters were tuned to determine the optimal structural and functional partitioning of networks by MCL into PI multiprotein complexes and GC functional modules: namely, the MCL inflation value, the interaction scores, and the number of highly-connected hubs removed from consideration from each network. Optimization of these parameters resulted in a significantly greater functional homogeneity as compared with null models for both the PI and GC networks, as shown in panels (A) and (D), respectively. The distribution of members in the resulting final optimized sets of (B) putative complexes and (E) functional modules fits a power-law distribution. Conversely, while the degree of connectivity of the high-confidence PI network (C) follows a typical power-law distribution, the degree of connectivity of the GC network (F) shows an increased number of nodes with 10 to 100 interactions, deviating from a power law distribution.