Life Science Informatics

The Life Science Informatics department develops new approaches to produce highly specific information on diseases and individual patients.

After the sequencing of the human genome had been successfully completed, automatic instruments and computerized data analysis moved into the focus of biotechnology and medicine. On all levels, from molecular interaction to cellular function, tissue or organ structure, and the course of a disease in an individual patient, new instruments can produce information about the processes involved in a disease and can help to improve diagnosis and therapy.

This potential motivates our R&D in the field of information-intensive instruments using optical and electronic detection methods. We develop novel components, like fluidic microsystems to study cells and molecules, smart scanning microscopes and software for image analysis and object detection. We test and validate complete applications in cooperation with their users. We use our components to build application-specific systems that provide seamless integration in state-of-the-art network infrastructures and mobile access.

Computer scientists, engineers and natural scientists in two close collaborating groups work in our projects.

Groups and topics


High Content Analysis and software-intensive instruments (HCA)

Detection of structures, states and signals is a major component of automated instruments. The HCA group investigates detection methods and the information processing involved. A user-centered design approach guides the development of our technology: Users can adapt it without re-programming.


Biomolecular Optical Systems (BioMOS)

To build information-generating instruments you need to understand and control the interaction between assay and sensor system. The BioMOS group investigates microsystems to hold and treat biomolecular assays and multi-parametric, in particular optical sensor systems. We build systems incorporating these technologies and validate them in biological applications.


Big Data Applications in Life Sciences


Fraunhofer Medical Data Space