Human Cell Simulator

Whole-cell modeling enables a holistic and quantitative view of cell biology and allows performing in-silico experimentation which has a great potential in revolutionizing systems biology, synthetic biology, medicine and other applications in life science. However, modeling the entire cell is an extremely complex task and is heavily limited by our understanding of the biological systems. We take on this grand challenge of building a human cell simulator through recent advances in multi-omics data generation and artificial intelligence. Our aim is to use modern deep learning techniques — transformers, structure models such as AlphaFold, and diffusion/generative models — to integrate existing multi-omics datasets with massive amounts of newly generated live-cell and multiplexed imaging data, and to model cellular behavior through generative and predictive models.

This is the heart of our contribution to SciLifeLab’s Alpha Cell program: turning molecular maps of the human cell — grounded in the Human Protein Atlas and high-resolution imaging — into predictive, simulatable AI models. We build the data engines (Reef imaging farm, Self-driving Microscope) and the AI infrastructure (Hypha, BioEngine) that make whole-cell modeling at this scale possible.