Searching the overlap between network modules with specific betweeness (S2B) and its application to cross-disease analysis.

摘要: Discovering disease-associated genes (DG) is strategic for understanding pathological mechanisms. DGs form modules in protein interaction networks and diseases with common phenotypes share more or have closely interacting DGs. This prompted the development of Specific Betweenness (S2B) to find associated two related diseases. S2B prioritizes frequently specifically present shortest paths linking disease modules. Top scores identified overlap artificial network than 80% times, even incomplete noisy knowledge. Applied Amyotrophic Lateral Sclerosis Spinal Muscular Atrophy, candidates were enriched biological processes previously motor neuron degeneration. Some interacted cliques, suggesting molecular mechanisms a valuable tool DG prediction, bringing new insights into More generally, can be applied infer between other types modules, such as functional context-specific subnetworks. An R package implementing publicly available at https://github.com/frpinto/S2B .