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Despite the small module size, F C C outperformed the cubic lattice C in all simulated realizations.
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This is the result of a much smaller module size identified by GroupMiR.
The results clearly show that since the addition of a MeH material enables much smaller module sizes, it is advantageous for the thermal management of complex hydride based reactors and increases their flexibility.
The approach performs well when evaluated against similar tools and smaller overall module size allows for more specific functional annotation and facilitates the interpretation of these modules.
We note that the induced sparsity implies a poor identification power with regard to the resolution spectrum, especially for small and intermediate module sizes.
As a result, more sparsity implies lack of detection power for small and intermediate module sizes, whose overlaps are instead observed with CFinder.
Since module B is the by far largest module and highly enriched for F. graminearum responsive genes across all five lines, we further analyzed this module by splitting it into smaller submodules (deepsplit = 4; minimum module size = 10).
The smaller distribution of module sizes associated with Walktrap-GM highlights a more specific and informative set of biological interactions that facilitates interpretation of modules; where the functional annotation of larger modules that may otherwise be too general to be meaningful.
This larger module size identified low connectivity nodes which otherwise would have been missed using only the topological, hypergeometric analysis or smaller modules (i.e., only 2 or 3 nodes).
We find that large modules are less factorizable than small modules: there is a strong negative correlation between module factorizability F(A) and module size.
Note that with the chosen minimal module size of 30 genes, unassigned genes might still belong to smaller expression pathways.
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