Bioinformatics, Data Science
We are harnessing complex patient data for computational disease modeling and for developing data-driven tools that assist physicians in providing optimal patient care.
Translational bioinformatics deals with the analysis of novel types of patient data derived from cutting-edge technologies such as next generation sequencing. These investigations allow us to elucidate different aspects of cancer biology, with direct consequences for diagnosis and treatment. For example, our bioinformatics analyses were instrumental in identifying and characterizing some of the key mutated genes in melanoma, including RAC1 and NF1. In addition, our work has been directed towards studying the epigenetic regulation in cancer, and elucidation of drug resistance. We are currently performing bioinformatics research with a focus on single cell analysis of skin cancer and the development of high-sensitivity tests for treatment monitoring. Our data science research involves the use of deep learning for a broad range of topics including the prediction of hospital readmission, assessement of drug side effects, multimodal learning in radiology or Natural Language Processing in the health domain. Ultimately, we aim at bringing data-driven medicine into patient care at the USZ. To this end, we are working at the interface of research, patient care and hospital IT to harness routine data for the development and deployment of clinical decision support systems.Publications