BRIDGING: description

The Bridging Centrality is a node centrality index based on information flow and topological locality in networks. A bridging node is a node connecting densely connected components in a graph. It is the product of the betweenness centrality Cb and the bridging coefficient (BC) , which measures the global and local features of a node respectively. Specifically, the bridging centrality Cr(v) for node v of interest is defined by:

Cr(v) = BC(v) x Cb(v)

The betweenness is a measure of the global importance of a node that assesses the proportion of the shorttest paths between all node pairs that pass through the node of interest. The higher Cb(v), more number of shortest paths between all node pairs pass through the node v. So more information travel through the node v
The bridging coefficient of a node determines the extent how well the node is located between high degree nodes. It assesses the local bridging characteristics in the neighborhood. Intuitively, there should be more congestion on the smaller degree node since the smaller degree nodes have lesser number of outlets than the bigger degree nodes have. So if we consider the reciprocal of the degree of a node as the "resistance" of the node, the bridging coefficient can be viewed as the ratio of the resistance of a node to the sum of the resistance of its neighbours.
Critical bridging nodes, typically representing rate limiting points in networks and because they connect densely connected regions, have high "resistance": the higher Cr(v) signifies that more information flows through node v.

IN BIOLOGICAL TERMS

Bridging centrality can be used to break up modules in a network for clustering purpose.
Functional modules or physical modules in biological networks can be detected using the bridging nodes chosen by bridging centrality.
Second, it can be use to identigy the most critical points interrupting the information flow in a network, for network protection and robustness improvement purposes.
Third, in biological application, bridging centrality can be used to locate the key proteins, which are the connecting nodes among functional modules.