Sentence examples for based on edge betweenness from inspiring English sources

A novel algorithm BCe based on edge betweenness and vertex betweenness obtain overlapping structures by choosing the similarity threshold values between vertices pairs.

Here, the co-expression similarity S sj is the absolute value of the PCC between gene expression profiles × i, ×i (1) S ij = c o r (x i, x j ) Step 2. Module discovery using the weighted GN algorithm We applied the widely used weighted Girvan and Newman (GN) algorithm [ 20], a graph theory method based on edge betweenness algorithm.

Several algorithms, based on edge-betweenness centrality [ 28], on shortest path distances within a network, on the Statistical-Algorithmic Method for Bicluster Analysis (SAMBA) [ 29] or on the approximation mapping of network nodes into Euclidean space followed by fuzzy c-means clustering [ 30] were developed to identify dense sub-graphs and functional modules within the PPI networks.

An algorithm based on edge-betweenness (EB) [ 25] that involves the iterative removal of edges with the highest betweenness score to split the network into communities has been one of the very first attempts to use modularity maximisation for module detection.

E DGEB ETWEENNESS-BNM (E DGEB ETWEENNESS for biological network motif) algorithm removes edges based on its edge betweenness score.

Herein, we only consider transitive reduction based on edge removals.

Using the Girvan-Newman algorithm based on the edge betweenness and the concept of modularity to identify communities, we can understand the behaviour of many of the nodes of the simulation that do not reach any of the previous described regimes.

For example, Hartuv and Shamir used the minimum cut to remove edges recursively and developed a divisive algorithm HCS for mining highly connected clusters in networks [ 3], Girvan and Newman developed a divisive algorithm G-N based on the edge betweenness [ 4], Newman et al. proposed a fast agglomerative algorithm based on greedy strategy [ 5].

The betweenness-based node removal identifies critical nodes based on their betweenness, which measures the frequency with which a node falls on the shortest paths connecting pairs of other nodes [17].

We ranked genes based on betweenness values and compared the difference between the betweenness values for the real network and mean betweenness from 100 randomized networks for the same rank.

Four interface design strategies based on distance, betweenness, degree, and clustering coefficient are constructed.