Research summary
Recent advances in single-cell biotechnologies have greatly enhanced our ability to perform high-throughput molecular, functional and structural profiling of individual cells. This work is generating vast amounts of diverse data, but we don’t yet know how to effectively interpret these data to understand cellular behaviour in different biological contexts. Dr. Xin Tang, Canada Research Chair in Computational Cell Biology, aims to develop predictive, explainable and biologically informed artificial intelligence (AI) models to analyze single-cell data and uncover the principles that govern how cells function and interact.
By creating computational frameworks (such as virtual cells) and using AI agents that simulate how cells respond, he and his research team are building models that can analyze and interpret complex single-cell data across multiple types of biological data. Their findings will shed light on fundamental mechanisms in cell biology, systems biology, neuroscience and brain-computer interfaces, ultimately supporting biomedical breakthroughs.