Growing a Virtual Embryo with 3D Convolutional Models

Embryo Growth Simulation

This project trains foundational 3D convolutional models to reproduce embryogenesis in silico, capturing both cell-level gene expression prediction and 3D morphogenetic dynamics. The goal is to learn a generative model of embryonic development that jointly predicts how cells divide, differentiate, and spatially organize — bridging gene regulatory networks with tissue-scale morphology.

The approach leverages volumetric deep learning architectures to model the spatiotemporal evolution of developing embryos, learning from multi-modal developmental biology datasets that combine single-cell transcriptomics with 3D imaging.

I am one of the builders of the Virtual Embryo Challenge — a community benchmark for computational models of embryonic development.

Virtual Embryo Challenge — check it out and don’t hesitate to participate!

Status: More to come soon!