北京大学定量生物学中心
学术报告
题 目: Engineering Virtual Cells for In-Silico Perturbation and Therapeutic Discovery
报告人: Jun Ding, Ph.D.
Associate Professor in the Department of Medicine at McGill University
时 间: 6月15日（周一）13:00-14:00
地 点: 吕志和楼B101
主持人: 周沛劼
摘 要:
Recent advances in single-cell omics technologies have enabled the comprehensive characterization of cellular heterogeneity across healthy and diseased tissues. While these technologies provide unprecedented molecular resolution, a fundamental challenge remains: how can such data be transformed into predictive models that not only describe cellular states but also simulate disease progression and therapeutic responses?
In this talk, I will present our efforts to engineer virtual cells using deep generative artificial intelligence and single-cell multi-omics data. These virtual cells serve as computational representations of biological cells, capturing cellular states, disease-associated trajectories, and the underlying dynamics of cell fate transitions. By integrating molecular measurements across large-scale datasets, generative models can reconstruct disease landscapes and provide a foundation for computational experimentation.
Building upon these virtual-cell representations, I will discuss frameworks for in-silico perturbation that simulate the effects of genetic, molecular, and pharmacological interventions. By systematically perturbing disease-associated cellular states and evaluating their trajectories toward healthier phenotypes, these approaches enable the prioritization of therapeutic targets and candidate drugs without requiring exhaustive experimental screening.
Applications in pulmonary fibrosis and cancer demonstrate how virtual cells can uncover disease-driving mechanisms, identify candidate therapeutic interventions, and accelerate biomedical discovery. I will conclude by discussing future directions toward increasingly predictive virtual-cell systems capable of supporting disease simulation, therapeutic development, and precision medicine.
报告人简介：
Jun Ding is an Associate Professor in the Department of Medicine at McGill University, a Scientist at the Meakins–Christie Laboratories of the Research Institute of the McGill University Health Centre, an affiliated researcher at Mila – Quebec Artificial Intelligence Institute, and an FRQS Junior 2 Scholar in AI in Health Sciences.
His research lies at the intersection of artificial intelligence, computational biology, and medicine, with a focus on developing machine learning and deep generative AI methods to decode cellular dynamics from single-cell and spatial multi-omics data. His laboratory develops computational frameworks for disease modeling, virtual cell construction, and in-silico therapeutic discovery, with applications to pulmonary fibrosis, cancer, and other complex diseases.
Dr. Ding has developed several computational tools for single-cell and spatial omics analysis and has published in leading journals including Nature Biomedical Engineering, Nature Communications, Genome Biology, and Genome Research. His work has been supported by CIHR, NSERC, FRQS, and the Meakins–Christie Chair in Respiratory Research. His long-term vision is to build AI-powered virtual disease systems that enable predictive disease simulation and accelerate therapeutic discovery.
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