A systematic survey of centrality measures for protein-protein interaction networks

BMC Systems Biology

Table 1 Centrality measures. The centrality measures were represented in five groups depending on their logic and formulae

Distance_based	Degree-based	Eigen-based	Neighborhood-based	Miscellanous
Average Distance	Authority_score	Eigenvector centralities	ClusterRank	Geodesic K-Path Centrality
Barycenter	Degree Centrality	Katz Centrality (Katz Status Index)	Density of Maximum Neighborhood Component (DMNC)	Harary Graph Centrality
Closeness Centrality (Freeman)	Diffusion Degree	Laplacian Centrality	Maximum Neighborhood Component (MNC)	Information Centrality
Closeness centrality (Latora)	Kleinberg’s hub centrality scores		Subgraph centrality scores	Markov Centrality
Decay Centrality	Leverage Centrality			Shortest-Paths Betweenness Centrality
Eccentricity of the vertices	Lobby Index (Centrality)
Lin Centrality
Radiality Centrality
Residual Closeness Centrality

Note that the first column (i.e. distance-based centralities) was specified according to the definition of distance between vertices in graph theory. The second one (i.e. degree-based centralities) was defined based on the number of immediate neighbors of each node within a given network. Eigen-values of adjacency matrix was the main idea to classify the Eigen-based centralities. Furthermore, the concept of subgraph or community structure was proposed in the neighborhood-based centralities. Others were collected in the miscellaneous group. Remind that this grouping was just applied to have better visualizations.

ISSN: 1752-0509