We focus on the development and application of computational methods to investigate the molecular basis of disease. We explore multi-omics signatures to characterize health conditions and to stratify individuals in support of more effectives approaches for precision health and prevention.
More specifically we investigate the effect of diet on cardiometabolic health and determine characteristic metabolomic markers for stratification. We also develop and apply approaches to identify aggregation of health traits in families to better understand the environmental and genetic determinants of human health. The work is mostly application oriented, making use of the most appropriate tools for each task.
We are also committed to method development, by improving existing tools or developing new ones.
Computational Mass Spectrometry and Multi-Omics Data Integration
We implement software and methods for efficient processing and analyzing large-scale mass spectrometry (MS)-based metabolomics and proteomics data. This includes also methods for improved software interoperability, metabolomics data annotation and reproducible research. All developed software is provided as open-source and is integrated into the Bioconductor project. Further, we analyze the CHRIS metabolomics and proteomics data to evaluate influences of external factors on circulating blood proteins, metabolites and lipids.










