Dresden International Graduate School for Biomedicine and Bioengineering

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Computational Biology

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

Research Groups

Lutz Brusch Group

TUD ZIH

Spatio-temporal pattern formation in cells and tissues

© BIOTEC

Carlo Vittorio Cannistraci Group

TUD BIOTEC

Machine learning and complex-network science for personalized and systems biomedicine

M. Teresa Pisabarro Group

TUD BIOTEC

Computational approaches to functional genomics and rational engineering for target/drug discovery and biotechnology innovation

Ingo Roeder Group

TUD Medical Campus

Systems biology with applications in medicine, (stem) cell and developmental biology

© Katrin Boes

Carsten Rother Group

TUD Computer Science

Machine Learning, Computer Vision and Discrete Optimization for Bioinformatics

© BIOTEC

Michael Schroeder Group

TUD BIOTEC

Computational Drug Repositioning with Networks, Structures, Text & Ontologies

© Katrin Boes

Axel Voigt Group

TUD Mathematics

Mathematical Modeling and Numerical Simulation of Cells and Systems