Computational Biology addresses problems in biology, biomedicine and ecology through image analysis, theory, computer simulations and data visualization. In Dresden we focus on dynamic processes in cells and embryos but also on biomedical questions like tissue regeneration. An overarching question is how complex system behaviour at a large scale can emerge from simpler physical and chemical interactions at smaller scales. In close collaboration with experimentalists, our research groups develop and apply computational tools including image analysis and image quantification algorithms, model-based image segmentation and cell tracking algorithms, adaptive particle methods for spatiotemporal simulations, parallel high-performance computing, multi-scale mechanistic model simulations and deep learning. We are strong advocates of open source culture and community integration.
Image © Dahmann Group
Spatio-temporal pattern formation in cells and tissues
Machine learning and complex-network science for personalized and systems biomedicine
Computational approaches to functional genomics and rational engineering for target/drug discovery and biotechnology innovation
TUD Medical Campus
Systems biology with applications in medicine, (stem) cell and developmental biology
Computational Drug Repositioning with Networks, Structures, Text & Ontologies