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.
© Pisabarro Group
TUD ZIH Spatio-temporal pattern formation in cells and tissues
TUD Computer Science, TUD PoL Immersive Exploration of Multiscale Biological Data
TUD cfaed, TUD PoL Biological Algorithms: Spatio-temporal dynamics of cells and tissues
TUD BIOTEC 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
TUD BIOTEC Computational Drug Repositioning with Networks, Structures, Text & Ontologies