Jun Ding

We are a computational biology team at the Meakins-Christie Laboratories within McGill University's School of Medicine. Our research is dedicated to exploring cell dynamics across a spectrum of diseases, including developmental disorders, pulmonary diseases, and various cancers. Unravelling the complexities of cell dynamics is crucial for comprehending disease pathogenesis and developing new treatments. The vast heterogeneity in these diseases presents a significant challenge in uncovering new knowledge. Thanks to advancements in single-cell technologies that allow for detailed profiling of individual cell states, we now have unique opportunities to address these challenges, potentially leading to groundbreaking discoveries in fields like developmental and cancer biology. However, this influx of single-cell data also introduces complex challenges in creating computational models that can effectively link biomedical data to potential breakthroughs. Our primary focus is on developing innovative machine learning methods, particularly probabilistic graphical models, to analyze, model, and visualize single-cell (and/or bulk) omics data, with a preference for longitudinal or spatial data. By employing these computational models, we aim to gain a more profound understanding of cell dynamics in various biological systems. Ultimately, our work strives to enhance public health through machine learning-driven diagnostic and therapeutic innovations.