Modularity is one of these techniques.
Modularity was on average less preserved for S. cerevisiae networks (57% of the cases), due most likely to the increased complexity of regulatory interactions in eukaryotes.
But it's overseas where modularity is catching on in a big way.
However, modularity is based on the expected value of variables estimated on the null model, neglecting random fluctuations, which is why modularity can attain large values on specific partitions of random graphs [65] [67].
In the works of Parter et al. [ 6] and Kreimer et al. [ 15], modularity is based on the definition of Newman and Girvan [ 16].
Third, our test of modularity is based on RV coefficients between blocks of landmarks [ 61], while Parsons et al.[ 45] investigated modularity using an approach based on a goodness of fit statistic, γ [ 77].
However, research on healthcare modularity is still scarce and research on modularity in the mental healthcare sector is even scarcer.
The impact of node duplication on modularity is more complicated.
Additionally it should be noted that L1 domain modularity is less clear cut on some autosomes.
