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First, we applied a network comparison algorithm [55] to compare the module-specific properties with the global properties of the brain networks.
To determine whether the module-specific network properties can be captured by the global topological properties in the brain functional network, we applied a network comparison algorithm recently proposed by [55].
In addition, by applying the list comparison algorithm to a similar dataset from mouse, we confirmed and extended the findings already reported in [ 17] about the close association of the two interventions in mouse.
Care should be taken however to avoid spurious conclusions arising from multiple comparisons when repeatedly applying a coevolution algorithm to the same alignment recoded with multiple alphabets.
For these reasons, it is important to focus on the relative comparison from the raw data to CDM-transformed data, rather than the absolute prevalence when evaluating the impact of applying a consistent algorithm across sources.
Consistently, when we applied the list comparison algorithm to this dataset we detected in all three tissues a large and significant overlap between genes responding to both DR and resveratrol with changes in the same direction (heart: 977 genes; skeletal muscle: 1,733 genes; brain: 912 genes).
For this, we applied a filtering algorithm (which involves the comparison with randomized networks) to enrich highly connected genomic loci (Figure 2, Table S2).
We applied our novel list comparison algorithm to all pair-wise comparisons between the treatment/control pairs in this dataset and clustered interventions using a hierarchical clustering algorithm with a metric based on the degree of overlap between lists (see Material and methods).
This talking point applies a direct comparison between Clinton and her predecessors.
We apply a blockwise descent algorithm.
The script applies a maximum clique algorithm.
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