These results indicate that the attenuated pruning strategy of TRANSWESD based on edge weights is highly advantageous for reconstructing regulatory networks.
Using the filtering based on edge weights, such overly complex graphs can be reduced to focus on the really important associations which are most promising as targets for further research.
Finally, it is common to adapt the smoothness term at the pixel level by defining a weight based on edge intensity, effectively reducing the importance of the smoothness constraint in areas of possible motion discontinuities.
Herein, we only consider transitive reduction based on edge removals.
But not all nodes are equivalent: some are more important than others based on their edge weight, and, reasonably, connections from important nodes count more.
The confidence level computed in this work is based on the edge weight only.
Clustering with Overlapping Neighborhood Expansion (ClusterONE) [ 5] greedily expands clusters from seeded vertices to maximize a cohesiveness function, which is based on the edge weights within a cluster and the edge weights connecting the cluster to the rest of the network.
The algorithm then sorts all edges of the graph (equivalently, pairs of the fragments) based on the edge weights and stores the results in D. An initial partition is formed by placing the two fragments with largest inter-fragment distance (associated with the heaviest edge in G) into two separate partition sets C1 and C2.
Then, we divide the neighboring vertices of u into five bins based on their edge weights: (0, 0.2], (0.2, 0.4], (0.4, 0.6], (0.6, 0.8] and (0.8, 1]. We search from the highest weight bin (0.8, 1] to the lowest weight bin (0, 0.2].
