Rothenberg et al. [33] observed the information centrality and distance metrics (eccentricity, mean, and median of the path length between any two vertices) to be not so strongly correlated with the degree and betweenness centrality metrics.
A number of centrality-based measures have been proposed in the network literature, such as degree centrality, centrality beyond nearest neighbors (e.g., Katz centrality, eigenvector centrality, subgraph centrality, PageRank centrality, and vibrational centrality), closeness centrality, betweenness centrality, and information centrality; see Estrada (2012) for details.
We will also evaluate more useful parameters such as subgraph centrality and information centrality to calculate the node importance in both directed and undirected networks [ 58].
These centrality measures were compared with other typical centrality measures: Local Average Connectivity- (LAC-) based method, Network Centrality (NC), Subgraph Centrality (SC), and Information Centrality (IC).
The topological features include degree centrality, betweenness centrality, closeness centrality, subgraph centrality, eigenvector centrality, information centrality and edge clustering coefficient centrality in PPI network, which are calculated by the centrality methods DC, BC, CC, SC, EC, IC and NC, respectively.
Information centrality IC): The information centrality IC i) of node i in a is defined as [ 26]: (5) I C (i ) = [ 1 n ∑ j 1 I i j ] - 1, where n is the number of nodes in graph G and I ij = (r ii + r jj - r ij ) - 1, where r ij is the element of matrix R. Let D be a diagonal matrix of the weighted degree of each node and J be a matrix with all its elements equal to one.
Greater application of this approach together with the development of new social network measures could provide valuable information on the centrality of individuals in these networks and their network behavior.
Figure 1 illustrates the difference between dense and sparse operations and introduces two types of central positioning hubs and brokers [(see Borgatti and Everett 1992, 2006) or for a more information about network centrality and associated metrics visit https://en.wikipedia.org/wiki/Centrality or http://www.faculty.ucr.edu/~hanneman/nettext/C10_Centrality.html].
Functional cartography was extended to include leverage, degree, betweenness, or eigenvector centrality information as the 3rd axis.
So, we developed a hybrid presentation in which the node centrality information is superimposed on the evaluated MST.
The TO measure offers different, complementary information than the centrality indices.
