BIMSA > Seminar on Bioinformatics scFed: federated learning for cell type classification with scRNA-seq
scFed: federated learning for cell type classification with scRNA-seq
Organizer
Stephen S-T. Yau
Speaker
Nan Sun
Time
Tuesday, April 30, 2024 2:30 PM - 3:00 PM
Venue
理科楼A-304
Abstract
The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and complexity in biological tissues. However, the nature of large, sparse scRNA-seq datasets and privacy regulations present challenges for efficient cell identification. Federated learning provides a solution, allowing efficient and private data use. Here, scFed was introduced, and it is a unified federated learning framework that allows for benchmarking of four classification algorithms without violating data privacy, including single-cell-specific and general-purpose classifiers.
Speaker Intro
孙楠目前是北京雁栖湖应用数学研究院的博士后。她的研究方向包括生物信息学、机器学习和应用数学，在The Innovation, Computational and Structural Biotechnology Journal, BMC Bioinformatics, Frontiers in Cellular and Infection Microbiology, Journal of Computational Biology, Genes等期刊发表多篇论文，参与多项国家自然科学基金及北京市自然科学基金项目，主持中国博士后科学基金第78批面上资助。