The objective of our research group is to acquire the basic knowledge necessary to develop new therapies against diseases affecting the liver. For that, we use stem cells to model embryonic development in vitro and to produce liver cells with an interest for cell therapy.

We sequence cells to understand how genetic mutations form and change cell states in health and disease.

The Gütig lab uses analytical and numerical modeling techniques to identify the computational principles underlying spike based information processing and learning in central nervous systems and to understand how these principles are implemented by biological processes. Specifically, the lab focuses on the role of action potential timing in sensory…

Bone is an interesting tissue from the researchers view as it is able to regenerate after injury. However, even today and with an adequate treatment 5-20% of all fractured patients experience a delayed or non-union.

Tissues in the musculoskeletal system are exquisitely designed with superb mechanical properties. The tissues are also able to adapt to withstand changing mechanical conditions. The Computational Mechanobiology Group is focused on understanding these two exciting features. Using computer modeling techniques, we seek to understand the mechanical…

The Medical Omics lab aims to improve healthcare and basic research by providing artificial intelligence-driven tools for the analysis of large biomedical datasets. For comprehensive insights in disease entities, we aim to include multiple layers of data, such as single-cell RNA sequencing, methylomics data and medical imaging. In close…

Rapid advances in molecular biology technologies are leading to a data explosion in biomedical research and clinical diagnostics. The goal of our department is to develop new and targeted ways to analyze and evaluate these data sets in order to implement innovations that benefit patients. For instance, it is desirable to make information from…

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Common metabolic disorders such as obesity, insulin resistance and type 2 diabetes have both environmental and genetic causes. We now know that many sections of the genome influence the risk of weight gain or adverse fat distribution, in addition to the important roles played by lack of physical activity and excessive intake of high-calorie foods.…