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In this proof-of-concept study, we demonstrate that a subnetwork alignment approach can reveal previously uncharacterized members of the subnetworks, which opens new opportunities to identify potential therapeutic targets and provide new insights into parasite biology, pathogenesis and virulence.
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Glencore needs to demonstrate that an I.P.O.
We demonstrate that one subnetwork can develop localized and oriented components.
There we analyzed a subnetwork of the transcriptional regulatory network and could demonstrate that the obtained subnetwork is statistically significant with respect to several properties, e.g., the number of periodic genes reachable from the strongly connected component (SCC).
The evaluation of our method on published patients' drug response data demonstrate that optimally discriminative subnetwork markers yield both greater and more robust classification performance compared with single gene markers and other subnetwork markers.
The results demonstrate that our coherent subnetwork approach is able to identify novel drug indications and highlight their molecular basis.
In this study, we first expand the mathematical compensation analysis beyond the 1-component and 2-component networks, so that the analysis includes gene networks of any size (N-component networks), demonstrating that a necessary condition for dosage compensation in such networks is the existence of a 2-component subnetwork with an activator and an inhibitor.
This demonstrates that subnetwork hubs represent key regulators relevant to the experimental conditions tested.
Chuang et al. (2007) demonstrated that subnetwork markers are more robust, i.e. their results tend to provide more reproducible results across different cohorts of patients.
Furthermore, we demonstrate that the drug-induced cell death subnetwork can be computationally inferred using a Bayesian network modeling approach.
Taken together, these results demonstrate that all of the proteins in the MD subnetwork are expressed in the retina.
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