Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the...
To provide greater clarity, several exemplars of network metrics are provided (e.g., degree of centrality, betweenness centrality, eigenvector centrality, closeness centrality, and PageRank), along with a sample table of publication ranking that can be curated across different centrality measures (...
Unfortunately, just the most fundamental measures, that serve as basis for higher measures, are the hardest to calculate, as shown in the next section. 1.4. Hierarchy of measures The hierarchy diagram (Fig. 2) shows computational dependencies between a few complex network measures, each computed ...
While betweenness centrality may say something about who controls the flow of information in a network, closeness centrality is another measure that may say something about how fast or how far information from a node spreads. Formally, closeness centrality measures how close a node is to all the...
While betweenness centrality may say something about who controls the flow of information in a network, closeness centrality is another measure that may say something about how fast or how far information from a node spreads. Formally, closeness centrality measures how close a node is to all the...
Betweenness centrality, connectivity, network efficiency, and closeness centrality are topological properties which aim to evaluate the most important segments or nodes and the ability of a system to remain connected. Betweenness centrality assesses how often a node v is positioned along the shortest ...
The S-curve specification allows us to calculate the estimated Take off time as a linear combination of the two parameters Midpoint and Alpha of the estimated trajectory: Take off = Midpoint-2.2*Alpha. Other take off thresholds beyond 10%, can be calculated in a similar fashion using linear...
The closeness centrality range of the network before optimization is from 0.23 to 0.10, and after optimization is from 0.07 to 0.18. There are 57 nodes with a network clustering of 1 before optimization, and 91 such nodes after optimization. There are three nodes with a betweenness centrality ...