The Medical Bioinformatics group conducts research with a strong emphasis on translational science with the ultimate goal of improving human health. The focus is on gaining a fundamental understanding of molecular function from genes and proteins to pathways to entire systems, using innovative computational strategies. 

To do this, we are developing and using new methods for integrative analysis of the rapidly growing data from modern -omics experiments combined with the large volumes of electronically available patient information.

This is essential for the successful integration of biomedical and clinical data, ultimately leading to better treatments for today’s patients and accelerating progress in making medical discoveries. Our main goal is to transform found biological insight directly into diagnoses, prognosis, and therapeutics that improve our ability to detect and treat human disease. We have been working on developing methods to effectively correlate disease-specific phenotypic information with available very large data-sets (big-data) from various -omics experiments. Current approaches include network-based data integration and analysis and compressed-sensing based methods leading to new ideas for sparse classification.