Stefan Semrau Lab (Quantitative Single-Cell Biology)
We study cell-fate decision-making using embryonic stem cells as a model system. Stem cells integrate a large number of cues to direct their development into a great variety of cell types.
Using single-cell transcriptomics and single-molecule microscopy in combination with machine learning and mathematical modeling we seek to unravel the dynamics of the decision making process and understand the interplay of internal factors (epigenetics, cell cycle, stochastic gene expression) and external factors (signaling molecules, cell-cell contacts, mechanical cues). We believe that the basic principles discovered through our research will be of great value for applications in regenerative medicine and the eradication of cancer stem cells.