Übersicht

Our lab integrates histomorphology, genomics and proteomics techniques with novel computational approaches including image analysis, bioinformatics and machine learning-based modeling to better understand tumor pathology and predict optimal precision therapies for cancer patients. A primary focus is to establish proteomics approaches in the identification of therapeutic targets and mechanisms of resistance to targeted therapy in tumor models and primary patient tissue to complement mutational profiling in cancer diagnostics. Moreover, we apply machine learning approaches to histological images and proteogenomic profiling data to predict molecular properties from histomorphology and infer pathologically relevant molecular mechanisms.