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Betweenness centrality. An undirected graph colored based on the betweenness centrality of each vertex from least (red) to greatest (blue). In graph theory, betweenness centrality is a measure of centrality in a graph based on shortest paths. For every pair of vertices in a connected graph, there exists at least one shortest path between the ...
Network science. In mathematics, computer science and network science, network theory is a part of graph theory. It defines networks as graphs where the vertices or edges possess attributes. Network theory analyses these networks over the symmetric relations or asymmetric relations between their (discrete) components.
Procedures to identify association, communities, and centrality within nodes in a biological network can provide insight into the relationships of whatever the nodes represent whether they are genes, species, etc. Formulation of these methods transcends disciplines and relies heavily on graph theory, computer science, and bioinformatics.
For large graphs, the minus one in the normalisation becomes inconsequential and it is often dropped. As one of the oldest centrality measures, closeness is often given in general discussions of network centrality measures in introductory texts [6] [7] [8] or in articles comparing different centrality measures.
Clique problem. The brute force algorithm finds a 4-clique in this 7-vertex graph (the complement of the 7-vertex path graph) by systematically checking all C (7,4) = 35 4-vertex subgraphs for completeness. In computer science, the clique problem is the computational problem of finding cliques (subsets of vertices, all adjacent to each other ...
where s max is the maximum value of s(H) for H in the set of all graphs with degree distribution identical to that of G. This gives a metric between 0 and 1, where a graph G with small S(G) is "scale-rich", and a graph G with S(G) close to 1 is "scale-free". This definition captures the notion of self-similarity implied in the name "scale-free".
In the mathematical area of graph theory, a clique (/ ˈkliːk / or / ˈklɪk /) is a subset of vertices of an undirected graph such that every two distinct vertices in the clique are adjacent. That is, a clique of a graph is an induced subgraph of that is complete. Cliques are one of the basic concepts of graph theory and are used in many ...
In graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, super-spreaders of disease, and brain networks.