Updated: Wed, 10/02/2024 - 13:45

From Saturday, Oct. 5 through Monday, Oct. 7, the Downtown and Macdonald Campuses will be open only to McGill students, employees and essential visitors. Many classes will be held online. Remote work required where possible. See Campus Public Safety website for details.


Du samedi 5 octobre au lundi 7 octobre, le campus du centre-ville et le campus Macdonald ne seront accessibles qu’aux étudiants et aux membres du personnel de l’Université McGill, ainsi qu’aux visiteurs essentiels. De nombreux cours auront lieu en ligne. Le personnel devra travailler à distance, si possible. Voir le site Web de la Direction de la protection et de la prévention pour plus de détails.

Jun Ding

Academic title(s): 

Assistant Professor
Department of Medicine

Associate Member
Department of Biomedical Engineering

Jun Ding
Contact Information
Email address: 
jun.ding [at] mcgill.ca
Department: 
Experimental Medicine
Areas of expertise: 

Our lab focuses on studying cell dynamics in various biological processes in many diseases (e.g., developmental disorders, pulmonary diseases, cancers). Decoding cell dynamics is essential for understanding the pathogenesis of diseases and finding novel therapeutics. The existence of enormous heterogeneity in those diseases makes it challenging to decipher the unknown. The advancing single-cell technologies that profile individual cell states provide unprecedented opportunities to tackle this problem, which could drive biological discoveries and medical innovations in various fields (such as developmental and cancer biology). However, single-cell data presents numerous new challenges in developing computational models that bridge biomedical data and potential discoveries. My primary research is to develop machine learning approaches (particularly probabilistic graphical models) to jointly analyze, model, and visualize single-cell (and/or bulk) omics data (preferably longitudinal or spatial). Such computational models will be used to help us derive a deeper understanding of the cell dynamics in different biological systems, which will eventually benefit public health with machine-learning-driven new diagnostic and therapeutic strategies.

Research areas: 
Biomedical Modelling
Bioinformatics and Computational Biology
Area(s): 
Genomics and Functional Genomics
Cell Manipulation
Biomarkers
Machine Learning
Single Cell analysis
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