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DeepEmbryo aims to understand early embryo development by using deep learning techniques on high-resolution 3D microscopy data. The project focuses on identifying forces shaping embryos and how cells coordinate during development across various animal species.
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…
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
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