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The hierarchical clustering of the genera was based on the similarity between their pathway profiles without using the taxonomic or phylogenetic information.
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This association is an example of a negative relationship between two pathways; i.e., basically, their pathway profiles are negatively correlated.
Finally, correlations between breast cancer subtypes and other diseases were calculated by comparing their pathway profiles using hypergeometric statistics.
Having determined that the compounds could be grouped according to their mRNA abundance profiles, we hypothesized that these groups could be recapitulated from their pathway profiles.
Ye integrated known drug target information and proposed a disease-oriented strategy for evaluating the relationships between drugs and specific diseases based on their pathway profile [ 15].
The 1206 genera were hierarchically clustered based on their metabolic pathway profiles and 706 metabolic pathways were clustered based on their distribution across the genera (see Figure 2).
The metabolic pathway profiles of genomes were superimposed on their phylogenetic tree to assess the phylogeny-function correlation.
Using a human model incorporating varying infection severity, we found important differences in pathway profiles of circulating leukocytes between asymptomatic, mild and severe influenza infection.
Once pathway profiles have been defined, these are used to find connections between pathways.
We then compute the similarity between two genes based on the overlap between their GO profiles.
For all such gene pairs, we already have two correlation coefficients: one between their transcription rate profiles and one between their mRNA abundance profiles.
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