Date(s) - 25/09/2018
11 h 00 min - 12 h 00 min
The conditions of an immune disease can often be represented by interaction graphs, but how those complex graphs are susceptible to interventions is still of utmost importance in areas such as reprogramming therapeutics. In this sense, module identification is an essential step towards understanding the whole graph architecture. The consideration of a general class of node dissimilarity measures related to the notion of topological overlap enables detecting “driver” genes with high specificity in these modules. These module regulators can affect other nodes, potentially causing the entire system to change behaviour or fail. We provide a geometric framework based on singular manifolds explaining such situations in inflammatory bowel disease (IBD). IBD are important chronic disorders of the gastrointestinal tract which incidence is dramatically increasing worldwide. Our approach models those scenarios by reinterpreting the nonlinear dynamics intrinsic to real systems captured as compensatory responses to perturbations of a graph on its manifold of definition. Thus, we are able to reconfiguring the immune system to a desired target state. We illustrate the effectiveness of the strategy through the identification of potential drivers controlling the dynamic of IBD gene co-expression networks resulting from two high throughput proteome screenings.