Probabilistic functional integrated networks for drug repurposing

Traditional drug discovery is a complex, time-consuming, high-risk, and expensive process. One alternative to discovering novel entities is drug repositioning which aims to find new uses for existing drugs. This strategy is efficient, economical, and less risky. The computational approaches to drug repurposing often rely on different data sources integrated into a single database or network. However, the quality of the integrated network depends on the quality of the individual data components. So the main challenge in constructing accurate networks lies in the evaluation of the data quality prior to integration.

In this talk, I will describe an integration technique that incorporates data assessment - Probabilistic Functional Integrated Networks (PFINs). I will discuss the main steps needed to apply PFINs and show how PFINs could be used in context of disease-gene associations.