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The clustering coefficient of the individual nodes and of the entire network can be used to obtain important information about the type of network, grouping (or classification) of nodes, and identification of the most significant nodes.
We call the set of most significant nodes, in terms of the weights returned, an Information Transduction Module (ITM).
In CentiScaPe, computed centralities can be easily correlated between each other or with biological parameters derived from the experiments in order to identify the most significant nodes according to both topological and biological properties.
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This node can be regarded as the most significant node for OC relevant miRNA regulation.
Interestingly, this module shows HLA-DRA as the most significant node.
When there were multiple nodes within a lineage fulfilling these criteria, only the most significant node was retained.
Although the only gene consistently found associated to MS in this region is HLA-DRB1, the module shown lists another gene, HLA-DRA, as its most significant node.
The most highly significant nodes thus derived are denoted as key nodes.
Here, hemoglobin A1c was not among the most structurally significant nodes, although it was suggestively positioned between insulin dose and triglycerides in Figure 1.
In addition, undirected networks do not have a clear pattern as the motif size exceeds five nodes, because some networks continue to contain more of the most significant three-node motif and some contain fewer.
When the motif size increased to five nodes, 15 out of 17 networks contained at least one instance of the most significant three-node motif.
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