From: IPMC

Will give a seminar entitled:

The Human Lung Cell Atlas

Since 2015, we have been contributing to the creation of comprehensive reference maps of human lung cells^1,2. These cellular atlases help us to better understand healthy respiratory pathways and improve the diagnosis, monitoring, and treatment of fatal lung diseases³. In this talk, I will discuss the process of single-cell atlas reconstruction, beginning with our first large-scale atlas containing 80,000 cells¹. I will then go on to discuss the Human Lung Cell Atlas, which integrates 2.4 million cells⁴, and conclude with our latest atlas, which includes cells sampled from early-stage COPD (chronic obstructive pulmonary disease) patients. Finally, from a bioinformatics perspective, I will address how deep learning models have revolutionized our single-cell atlas reconstruction methods and how foundation models, such as scGPT⁵, are poised to become ubiquitous tools for all atlas-related tasks.

1 – Deprez, M. et al. A Single-Cell Atlas of the Human Healthy Airways. Am. J. Respir. Crit. Care Med. 202, 1636–1645 (2020).
2 – Ruiz García, S. et al. Novel dynamics of human mucociliary differentiation revealed by single-cell RNA sequencing of nasal epithelial cultures. Development 146, dev.177428 (2019).
3 – Sungnak, W. et al. SARS-CoV-2 Entry Factors are Highly Expressed in Nasal Epithelial Cells Together with Innate Immune Genes. Nat. Med. 26, 681–687 (2020).
4 – Sikkema, L. et al. An integrated cell atlas of the lung in health and disease. Nat. Med. 29, 1563–1577 (2023).
5 – Cui, H. et al. scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat. Methods 1–11 (2024) doi:10.1038/s41592-024-02201-0.

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