Food-borne risk factors for disease
Data mining, Food compounds, Ingredient discovery
Research aim
We develop and apply advanced data mining methods on cohort data, to identify and characterize yet undiscovered health-modulatory food compounds, with the aim to discover new food-derived leads for health interventions.
About us
To uncover the role of food compounds in health and disease, we combine data on the presence and levels of thousands of individual compounds in food from existing databases and develop strategies for linking this information with food intake data collected in cohort studies. This allows to map the intake of these compounds through food at individual chemical level. Subsequent combination with information on disease development, disease state, or disease course, allows to study the role of this wide spectrum of food compounds in health and disease.
This research is conducted in close collaboration with the Netherlands Organisation for Applied Scientific Research TNO. UMC Utrecht and TNO joined forces and closely collaborate in their research on food-borne risk factors for disease through a Research Chair at the Medical Faculty of the Utrecht University. Access to mutual expertise, data and cohorts, and methods and facilities opens unique opportunities for the development and application of our innovative data science-based methods. TNO’s data science expertise, comprising of data warehousing, integration and analysis, such as mathematical modeling and machine learning, enables the complex data analyses needed for these integrated data sets.
With the discovery of beneficial and harmful compounds in our diet, we aim to provide authorities and companies with new leads for diet-based health promotion and disease reduction and development of preventive and therapeutic products.