Our work concentrates on the molecular link between
diet and health, with a focus on diabetes and obesity.

The main techniques that we employ are high throughput data analysis, network analysis and simulation, with the goal of integrating the three. As diabetes and obesity are multifactorial diseases with complex molecular pathology, we work with a range of biological data types, including genotyping, transcriptomic, and multivariate biomarkers. With integrated analysis of these data types, we aim to identify susceptibility markers of disease and networks of interacting genes/proteins that co-vary with health status and response to dietary intervention. Overlapping projects with systems pharmacology are an added value of our strategy, as they allow us to explicitly analyze disease onset/progression and response to clinical intervention in the context of genotype*environment (e.g., diet) interaction.