Computational Biomedicine & Disease Modeling

We develop mechanistic computational models of stem cell-driven processes in health and disease. The models help to compare mechanistic hypotheses, to estimate quantities which cannot be measured in experiments and to predict dynamics of complex systems. The computational models can be developed based on clinical data, experimental data and theoretical concepts. Examples include

• healthy hematopoiesis e.g., engraftment after stem cell transplantation, neutropoiesis during sepsis, clonal hematopoiesis
• impairment of blood cell formation and malignant cell expansion in acute myeloid leukemia (AML), myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS), chemotherapy
• clonal evolution and clonal selection
• stem cell regulation by systemic feedbacks and micro-environmental cues in the stem cell niche
• model-based risk-stratification in AML
• aging of hematopoietic, mesenchymal and neuronal stem cells