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The enrichment provides evidence that the modules are biologically meaningful.
Again, the enrichment provides evidence that the modules are biologically meaningful.
But we briefly mention that there is indirect evidence that most of the resulting modules are biologically meaningful.
Nevertheless not all the functional modules are biologically coherent entities in terms of co-expression, which will eventually hinder its detection with conventional methods of functional enrichment.
Many co-methylation and co-expression modules are highly significantly enriched with gene ontology categories, which provides indirect evidence that these modules are biologically meaningful.
In addition, we use a functional enrichment analysis of the resulting modules to provide indirect evidence that the modules are biologically meaningful.
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Thirty-seven modules had enrichment of at least one type of biological gene set (i.e., protein domain, biological pathway, protein complex or transcription unit), and 21 modules were related to at least one biological pathway, which indicated that the modules were biologically meaningful.
While integrating of gene expression information into identification of gene modules is biologically meaningful, gene-network based methods are rarely satisfactory because they either focus on small networks by using the greedy subgraph search algorithm [ 17, 18] or focus on detecting non-overlapping subnetworks [ 16, 19, 20].
Both models are biologically inspired.
In each case, the learned modules and pathways are biologically sound, and lead to novel insights, emphasizing the power of integrated probabilistic models.
However, the other modules are also biologically informative.
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