The historical information-based algorithms usually use the community structure and centrality as the basic information [19].
The interactions in PPI networks are not random: proteins function in modules, therefore we should be able to use the community structure of the network to identify true positive and true negative interactions, unless this structure is completely destroyed by noise.
Moreover, using the bacterial community structure analysis method, where the consortia consist of different PAH-degrading bacteria, the information from the PCR-DGGE profiles could be used in the bioremediation of PAHs in the future.
Other algorithms can be used to extract the community structure of a graph, like the leading eigenvector [42], the multi-level modularity [43] or the spin-glass [44], and refined methods can be used to which one gives the most significant results, like e.g. a consensus analysis [45].
The neutral model was used to identify whether the community structure shows divergence, convergence or neutrality.
Then, we use neighaggre to find the community structure hidden in MNs.
The tool PHAge Communities from Contig Spectra (PHACCS) assesses the biodiversity of uncultured viral communities by mathematically modeling the community structure using the contig spectrum of metagenome assemblies (Angly et al., 2005).
This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC.
The community structure is used to describe the intimate relationship among nodes, and centrality is used to describe the active degree of nodes in the network.
The simulated distributions of clusters size match their empirical counterparts, which is far from being trivial given that no information about the community structure was used for the calibration.
