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 system 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. As a newly formed research group, we would like to take the grand challenge of building a human cell simulator through recent advances in multi-omics data generation and artificial intelligence. Our aim is to use recent deep learning techniques such as convolutional neural networks, transformers, AlphaFold and diffusion models to analysis existing multi-omics dataset, combining them with massive amount of newly generated live cell, multiplexed images, to model cellular behavior through generative and predictive models.