After selecting most connected component, we finally obtained PPINet, GENet and GONet networks with size as shown in Table 1.
This was subsequently confirmed by the following bow-tie structure analysis that revealed CPP metabolites were enriched in the giant strong component (see Additional file 2) which was the most connected part in the network.
For instance, although it is possible to limit the solution to connected subgraphs (Koch, 2001), using association graphs it is not easy to further relax the constraints on their connectedness, such as limiting the solution to contain at most three connected components.
Most of the connected components obtained were small, in particular, the number of orphans doubled; see Figure 11.
Most CSF voxels formed large connected components that were found automatically, so the manual post-processing of the classified 3D image to locate CSF voxels was moderate.
The remaining most significant categories resulted in five connected components in the Gene Ontology graph that are listed in Table 3.
This similarity network retained 131,162 environmental sequences, and yielded 82 connected components: adding environmental sequences made most of the nuclei grow into independant connected component, but a in a few cases two nuclei were united into the same component.
The number of connected components indicates the connectivity of a network – a lower number of connected components suggest a stronger connectivity.
The most straight-forward, identifiable subgraphs are the 'singly connected' components that arise during the graph process.
Focussing on the connected components we identify which geographical regions most of the observed network stems from.
