About the lab

The Claassen Lab at the University of Tübingen develops explainable quantitative models in systems medicine by integrating high-dimensional single-cell omics and imaging data with machine learning approaches.

Mission

Our ultimate goal is to elucidate intra- and intercellular mechanisms of rare cell subsets and uncover their association with organism-level phenotypes. To this end we develop machine learning methodology, aiming at identification of molecular patterns and mechanisms from single-cell data for basic life science research and actionable targets for precision medicine.

Research approach

We combine experimental and computational strategies to analyze single-cell measurements in immune and cancer biology. A core component of our work involves developing custom algorithms and statistical tools tailored to the unique challenges of high-dimensional data. Further we build on our own multiplexed tissue imaging platform for generation of our own experimental data for exploration and validation. These methods enable us to bridge multiple scales of biological organization - from molecular mechanisms within individual cells to their collective behavior in tissues.