Rapid advances in microscopy and single cell sequencing make it possible to study embryonic development with high spatiotemporal resolution. But extracting relevant biophysical information from these data remains a major challenge. We combine physical and numerical modeling to understand how cells self-organize to form an early embryo from a single egg. Our research aims to provide a computational platform to simulate embryogenesis from experimental data. It inaugurates a new field at the border between artificial intelligence, physics and biology, with possible spin-offs in reproductive and regenerative medicine.
