Table 1 The relationships between PeC and fifteen other centrality measures for predicting the top 100 proteins.
Centrality measures (Mi) | |PeC∩ Mi| | |M i - PeC| | Non-essential proteins in {M i - PeC} | Percentage of non-essential proteins in {M i - PeC} with low PeC |
|---|---|---|---|---|
Degree Centrality (DC) | 18 | 82 | 44 | 54.5% |
Betweenness Centrality (BC) | 16 | 84 | 47 | 51.1% |
Closeness Centrality (CC) | 16 | 84 | 51 | 56.9% |
Subgraph Centrality(SC) | 11 | 89 | 59 | 64.4% |
Eigenvector Centrality(EC) | 11 | 89 | 59 | 64.4% |
Information Centrality(IC) | 17 | 83 | 47 | 55.3% |
Bottle Neck (BN) | 16 | 84 | 53 | 45.3% |
Density of Maximum Neighborhood Component (DMNC) | 12 | 88 | 42 | 42.9% |
Local Average Connectivity-based method (LAC) | 34 | 66 | 37 | 59.5% |
Sum of ECC (SoECC) | 37 | 63 | 31 | 54.8% |
Range-Limited Centrality (RL) | 17 | 83 | 42 | 54.8% |
L-index (LI) | 13 | 87 | 55 | 58.2% |
Leader Rank(LR) | 16 | 84 | 46 | 52.2% |
Normalized α-Centrality (NC) | 11 | 89 | 59 | 64.4% |
Moduland-Centrality(MC) | 11 | 89 | 57 | 66.7% |