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Briefings in Bioinformatics|March 4, 2023
scGAD: a new task and end-to-end framework for generalized cell type annotation and discoveryYuyao Zhai, Liang Chen, Minghua DengBriefings in Bioinformatics|February 17, 2024
scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq dataYuyao Zhai, Liang Chen, Minghua DengBriefings in Bioinformatics|April 28, 2024
scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics dataYuyao Zhai, Liang Chen, Minghua DengBioinformatics (Oxford, England)|October 24, 2020
Single-cell RNA-seq data semi-supervised clustering and annotation via structural regularized domain adaptationLiang Chen, Qiuyan He, Yuyao Zhai, et al.Frontiers in Genetics|May 5, 2020
Single-Cell Transcriptome Data Clustering via Multinomial Modeling and Adaptive Fuzzy K-Means AlgorithmLiang Chen, Weinan Wang, Yuyao Zhai, et al.Journal of Bioinformatics and Computational Biology|October 27, 2020
Direct interaction network inference for compositional data via codalossLiang Chen, Shun He, Yuyao Zhai, et al.NAR Genomics and Bioinformatics|February 12, 2021
Deep soft K-means clustering with self-training for single-cell RNA sequence dataLiang Chen, Weinan Wang, Yuyao Zhai, et al.Genes|July 18, 2020
Integrating Deep Supervised, Self-Supervised and Unsupervised Learning for Single-Cell RNA-seq Clustering and AnnotationLiang Chen, Yuyao Zhai, Qiuyan He, et al.Bioinformatics (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 DengPageof 946