Graph Contrastive Learning as a Versatile Foundation for Advanced scRNA-seq Data Analysis
Zhenhao Zhang, Yuxi Liu, Meichen Xiao, Kun Wang, Yu Huang, Jiang Bian, Ruolin Yang, Fuyi Li
This paper introduces scSimGCL, a graph contrastive learning framework for scRNA-seq data that improves cell clustering through self-supervised pretraining and high-quality representation learning.
Briefings in Bioinformatics · Sep 23, 2024Peer-reviewedBioinformatics