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These locations each consisted of a set of one to five connected edges forming a path in the road network.
Frequency denotes the number of differentially connected edges detected in GSE2990 and GSE6532.
In the proposed method, an original network structure was compressed by iteratively contracting identical edges and sets of connected edges.
Adjacent (connected) edges that share many neighbors were defined as similar and were thus clustered together (Ahn et al., 2010), outperforming different node clustering methods, including a method that allows for the group overlap.
The density region of one density node is defined as its immediately connected neighbors, except those without any connected edges to any other neighbors.
Therefore, we can conclude that in realistic scenarios, though we are not able to identify all truly differentially connected edges, those edges that are declared as differentially connected between states are very likely to be true findings.
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Edge images are, in turn, formed by sets of connected edge pixels.
It is known that not all arrangements of six square panels connected edge-to-edge will fold into a cube.
Therefore we take ±40 as the threshold, which gives 72.34% sensitivity and 99.90% specificity for detection of a differentially connected edge.
In this rendering, each triangle formed by three mutually connecting edges represents a triad identity.
In graph theory, the network is a graph consisting of a set of nodes with connecting edges.
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