Single-cell genomics is the study of the individuality of cells using “omics” approaches, such as genomics, epigenomics, proteomics, metabolomics and more. A rapidly evolving field, single-cell genomics enables scientists to study tissue cells at single-cell resolution. But scientists still face the challenge of how to combine single-cell measurements and computational modelling to understand how cells are organized in tissues.
To overcome this challenge, Dr. Jiarui Ding, Canada Research Chair in Machine Learning and Single-cell Analysis, is working at the intersection of computing and biology to build mathematical models that can explain complex phenomena in biology. More specifically, he and his research team are using the human esophagus to study tissue architecture and function in healthy and diseased tissues. Their findings will have a broad impact on biological data analyses as well as data-driven clinical decision-making.