Turlier Lab

Research focus

ERC Starting Grant · 2020

Reverse-engineering the development of embryos with physics-informed machine learning

Embryogenesis is archetypal of a self-organized process, where the emergence of a complex structure stems from the interaction of its elementary parts. Progress in imaging and molecular genetics allow us to delve into embryos at unprecedented spatiotemporal resolutions, but extracting biophysical information from this complex multidimensional data is a highly technical challenge. As a result the principles of multicellular self-organization remain far from understood. DeepEmbryo proposes to fill this gap by pioneering the use of deep learning to reverse-engineer early embryo development directly from high-resolution 3D microscopy movies. Focusing on four animal groups (mammals, ascidians,…

From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.