Cluster Edge Betweenness
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Clusteredgebetweenness performs this algorithm by calculating the edge betweenness of the graph removing the edge with the highest edge betweenness score then recalculating edge betweenness of the edges and again removing the one with the highest score etc.
An algorithm for computing clusters community structure in graphs based on edge betweenness.
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Cluster edge betweenness. Compute edge betweenness for all edges in current graph. Find go terms and the parents of those go terms for each go annotated protein in every cluster. Test the association between each go term and each cluster from a 2 by 2 contingency table. The connected components of the remaining network are the communities.
Clusteredgebetweenness performs this algorithm by calculating the edge betweenness of the graph removing the edge with the highest edge betweenness score then recalculating edge betweenness of the edges and again removing the one with the highest score etc. This algorithm works by iteratively following the 2 step process. Use the jung graph analysis framework to cluster the data using the edge betweenness algorithm. Clusteredgebetweenness performs this algorithm by calculating the edge betweenness of the graph removing the edge with the highest edge betweenness score then recalculating edge betweenness of the edges and again removing the one with the highest score etc.
Instead of trying to construct a measure that tells us which edges are the most central to communities the girvannewman.