The human adaptive immune system plays a vital role in the detection of potential pathogens, viruses, and diseases. In this research area, we passionately develop software to automatically analyze the immune repertoire of various species.

The identification of proteins in biological samples is essential for the understanding of cell processes and research on diseases. Therefore our research group strives for the development of algorithms to advance protein identification from mass spectrometry data.

Data science methods have become key technologies for solving biological, medical, and technical problems purely data based. We develop methods based on applied statistics and numerous machine learning approaches, including black box as well as white box methods.

Biomedical research often relies on imaging techniques and specifically designed image analysis workflows. We develop algorithms and software that analyzes high resolution microscopy images, especially focusing on algorithms for computer vision and machine learning.