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Detalle de: Singular manifolds of proteomic drivers to model the evolution of inflammatory bowel disease status

Title Singular manifolds of proteomic drivers to model the evolution of inflammatory bowel disease status
Abstract

The conditions used to describe the presence of an immune disease are often represented by interaction graphs. These informative, but intricate structures are susceptible to perturbations at different levels. The mode in which that perturbation occurs is still of utmost importance in areas such as cell reprogramming and therapeutics models. In this sense, module identification can be useful to well characterise the global graph architecture. To help us with this identification, we perform topological overlap-related measures. Thanks to these measures, the location of highly disease-specific module regulators is possible. Such regulators can perturb other nodes, potentially causing the entire system to change behaviour or collapse. We provide a geometric framework explaining such situations in the context of inflammatory bowel diseases (IBD). IBD are severe chronic disorders of the gastrointestinal tract whose incidence is dramatically increasing worldwide. Our approach models different IBD status as Riemannian manifolds defined by the graph Laplacian of two high throughput proteome screenings. It also identifies module regulators as singularities within the manifolds (the so-called singular manifolds). Furthermore, it reinterprets the characteristic nonlinear dynamics of IBD as compensatory responses to perturbations on those singularities. Then, particular reconfigurations of the immune system could make the disease status move towards an innocuous target state.

Apa Reference Morilla, I., Léger, T., Marah, A., Pic, I., Zaag, H. & Ogier-Denis, E. (2020). Singular manifolds of proteomic drivers to model the evolution of inflammatory bowel disease status. Scientific Reports, 10(1). 10.1038/s41598-020-76011-7
Doi 10.1038/s41598-020-76011-7
Publication Date 4 Nov 2020
Publication Type Article
Researcher Ian Morilla
Ontology Proteomics, Dynamical systems
Research Groups
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