Research
- Research Topics
- Cell Biology and Tumor Biology
- Stem Cells and Cancer
- Inflammatory Stress in Stem Cells
- Experimental Hematology
- Molecular Embryology
- Signal Transduction and Growth Control
- Epigenetics
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- Cell Morphogenesis and Signal Transduction
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- Signal Transduction in Cancer and Metabolism
- RNA-Protein Complexes and Cell Proliferation
- Systems Biology of Signal Transduction
- Areas of Interest
- Advancement of clinical proteomics for systems medicine
- Bridging from the single cell to the cell population – Epo-induced cellular responses and erythroleukemia
- Deciphering tumor microenvironment interactions determining lung cancer development
- Mechanisms controlling the compensation of liver injury and towards model-based biomarkers for early detection of liver cancer
- Application of dynamic pathway modelling for personalized medicine
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- Microrobots and Miniaturize Devices for Minimally-invasive Surgery
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Division of Artificial Intelligence in Oncology
Prof. Dr. Moritz Gerstung
The Gerstung lab investigates how tumours grow and change over time using AI and big data.
Cancer develops according to the rules of evolution — mutation and selection. Yet little is known about the timing of this process, the mechanisms by which mutations cause cancer cells to grow and how best to predict and influence the future course of this process.
Understanding these processes requires knowledge of large amounts of information at various scales. A cell’s genome comprises 6 billion base pairs of DNA. Thousands of genetic and epigenetic alterations of the DNA lead to a series of molecular cellular changes in each single cell. Further, tumours are an ecosystem of billions of mutant and normal cells that interact with each other via cellular contacts and signaling molecules.
Charting and modeling this information therefore requires sophisticated machine learning and AI algorithms. The primary focus of the lab is developing such algorithms and carrying out large scale data analyses to understand cancer evolution. The lab is also committed to contribute to generating genomic and molecular data at single and spatial resolution that form the basis of our research.
Specific research projects of the lab involve the establishment of a new spatial genomics platform for data generation and analysis. This will be key for decoding cancer evolution and unlock the secrets of the cancer ecosystem. We are also investigating how our knowledge about the natural history and origins of cancer can be used for early detection and cancer prevention.
Lastly, the lab investigates how mutations arise in single cells to understand the very first steps of cancer development.