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Modules are detected through the optimal division of the network.
However, the use of real data did not represent a clear scale-free network and consequently less clear modules are detected with lower correlations with the trait of interest.
Consequently, we have corroborated the analysis by investigating the resolution at which the modules are detected by each method and each dataset (evidence from two datasets has been reported in Figure 2, and from other datasets as supporting information).
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No main effects of the enhanced versions of intervention modules were detected.
Then, promoter regions in human genome were explored for modules and 328 genes containing the same modules were detected.
Modules were detected by dynamic hybrid cut.
Once modules were detected, different solutions were ranked according to a cost function and the optimal modularity (out of 10000 solutions for a range of between 2 and 6 modules) was used as the basis for hub classification.
Surprisingly, a mere 3 copies of dockerin modules were detected in the rumen metagenome (Table 3), which is most likely due to the rarity of cellulosome-based systems for plant cell wall degradation within the rumen community and the limits of the short pyrosequencing read lengths, as described by Brulc et al [53].
Alternatively, only three families of carbohydrate-binding modules and three dockerin modules were detected.
Modules were detected using a dynamic tree-cutting algorithm (hybrid mode, minimal module size of 100).
Recently, core modules were detected in the GBM data without using CNV information [ 49].
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