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Briefings in Bioinformatics|February 22, 2024
Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq dataHui Wan, Musu Yuan, Yiwei Fu, et al.Briefings in Bioinformatics|January 27, 2024
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq dataMusu Yuan, Hui Wan, Zihao Wang, et al.Bioinformatics (Oxford, England)|November 16, 2022
Clustering single-cell multi-omics data with MoClustMusu Yuan, Liang Chen, Minghua DengBioinformatics (Oxford, England)|October 8, 2021
scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasetsMusu Yuan, Liang Chen, Minghua DengFrontiers in Genetics|September 8, 2022
Clustering CITE-seq data with a canonical correlation-based deep learning methodMusu Yuan, Liang Chen, Minghua DengBriefings in Bioinformatics|June 27, 2024
scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinementQirui Guo, Musu Yuan, Lei Zhang, et al.Arxiv|September 24, 2024
Improving Tree Probability Estimation with Stochastic Optimization and Variance ReductionTianyu Xie, Musu Yuan, Minghua Deng, et al.Briefings in Bioinformatics|May 25, 2026
Out-of-distribution generalization enhances protein function annotation for low-homology sequencesYiwei Fu, Jiaxiao Chen, Haoyu Lin, et al.Bioinformatics (Oxford, England)|January 9, 2022
scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq dataHui Wan, Liang Chen, Minghua DengGenomics, Proteomics & Bioinformatics|January 7, 2023
scEMAIL: Universal and Source-free Annotation Method for scRNA-seq Data with Novel Cell-type PerceptionHui Wan, Liang Chen, Minghua DengPageof 51