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The relatively high density of the output modules (although this is not explicitly part of its underlying module definition) might come as no surprise.
But we find that many network concepts depend on the underlying module size.
Since the number of genes inside a module (module size) varies greatly among the modules, it is natural to wonder whether the reported relationships between network concepts are due to the underlying module sizes.
Specifically, by perceiving the cell or organism as a dynamic system composed of interacting functional modules which are defined as discrete entities whose functions are separable from those of other modules [ 23], the network information can help us to identify the underlying module structure.
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Our study offers two major conclusions: Three of the unmixing chains attain real-time performance (VD + OSP - GS + ULS) or close to it (VD + OSP - GS + ISRA and VD + N-FINDR + ULS) as the underlying modules VD, OSP-GS, N-FINDR, LSU and ISRA exhibit a high degree algorithmic concurrency that can be leveraged to yield efficient parallel implementations on current multi-core processors.
We show how the network information can help identify the underlying modules as formed by the refined hits that potentially explain the RNAi phenotype changes as observed by the screen experiments.
This may indicate a role for the proteins encoded by these genes in cross-talk between the processes underlying these modules, in this case between lipid metabolism (module C) and inflammation (module B).
Because genes in a co-expression module are likely to be regulated by a cohesive mechanism [ 8], we performed the functional category enrichment analysis for the modules against the gene sets of transcription factor targets in order to identify potential transcriptional regulatory mechanisms underlying the modules.
Modularity is important for organizations and the economy because the boundaries of organizational units and corporations are likely to match the boundaries of underlying technological modules.
Figure 3 shows an example of the PPI networks underlying different modules.
Most recent fMRI research conducted in combination with SP analysis has confirmed that the topography of the slow waves reveals the pattern of controlled activation (higher excitability) and deactivation (reduced excitability) of underlying cortical modules [59] [60].
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com