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This review has surveyed recent advances of engineered biological systems that utilize cell-cell communication to program bacterial group behaviors, covering both the basic communication modules and functional gene circuits that confer desired community-based dynamic behaviors.
On the systems level, they are studied to reveal modules and functional sub-networks [4], [5].
P values from this test were FDR-adjusted given the number of modules and functional categories tested.
Overrepresentation of canonical pathways and biological processes in modules was measured through Fisher's exact test and corrected for numbers of modules and functional categories tested.
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In addition, no clear relationship between p (representing the degree of enrichment of C-pairs in functional modules), and the functional hierarchy of such functional modules was found (Additional file 4).
Competitive protein-interaction tools [e.g. STRING (13)] are extended in GoSynthetic by information about protein function and modules, sub-modules and functional processes, both in a natural and an artificial engineering classification.
Sequence data from the first module and functional annotation from the second are matched using database similarity searches (BLASTX and BLASTN).
We give our performance metrics measuring how well the uncovered clusters correspond to protein complexes, BP functional modules and CC functional modules (Fig. 1) using the six studied algorithms applied to the HTP and Y2H networks.
For each of the three tasks we are considering (uncovering complexes, BP functional modules and CC functional modules), we utilize several measures to ascertain (i) how well each cluster maps to a known group and (ii) how well each group maps to a cluster.
We believe the higher density of the modules when compared with either size-equivalent random networks or with the entire network, the GO-term enrichments found in each module, their functional specialization (few shared GO terms between modules), and their functional homogeneity (similar or related functions within a module) strengthen the biological relevance of our IRES predictions.
KEGG MODULE [ 16] is a collection of pathway modules and other functional units designed for automatic functional annotation or pathway enrichment analysis.
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