Single cell analysis techniques are fundamental for understanding cellular function in health and disease. High-throughput multi-omics and perturbation technologies, lineage tracing, imaging, advanced data analytical, machine learning approaches and computation are advancing at speed and breaking new ground. This is enabling more sophisticated biological insights and opening up new applications across fields. With the latest single cell approaches, we can understand better than ever how cells interact, function in context, and change over time in the context of development, aging, and disease.

Open questions remain about how we can translate these fundamental insights and fully realize the therapeutic potential of single cell biology. This Symposium will bring together researchers working on a variety of biological systems and questions, and will cover the full experimental and analytical toolkit of single cell biology.

Themes

• The promise of AI and machine learning for interpreting single cells and their context
• Single cell analysis and genomics for diagnostics and therapeutic insights
• Spatial and temporal dynamics of cell populations
• Cell fate mapping, clonality and evolving concepts of cellular identity
• Learning by perturbing - challenges in high throughput analysis