* denotes equal contributions.
2026
Halo: a pretrained model for whole-cell segmentation from nuclei images in spatial transcriptomics
Xingyuan Zhang, Haotian Zhuang, Zhicheng Ji
Briefings in Bioinformatics 2026
Halo: a pretrained model for whole-cell segmentation from nuclei images in spatial transcriptomics
Xingyuan Zhang, Haotian Zhuang, Zhicheng Ji
Briefings in Bioinformatics 2026
Trajectory-guided dimensionality reduction for multi-sample single-cell RNA-seq data reveals biologically relevant sample-level heterogeneity
Haotian Zhuang, Xin Gai, Anru R. Zhang, Wenpin Hou, Zhicheng Ji, Pixu Shi
Bioinformatics 2026
Trajectory-guided dimensionality reduction for multi-sample single-cell RNA-seq data reveals biologically relevant sample-level heterogeneity
Haotian Zhuang, Xin Gai, Anru R. Zhang, Wenpin Hou, Zhicheng Ji, Pixu Shi
Bioinformatics 2026
PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns
Haotian Zhuang, Zhicheng Ji
Genome Biology 2026
PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns
Haotian Zhuang, Zhicheng Ji
Genome Biology 2026
2025
Identifying cell-type-specific spatially variable genes with ctSVG
Haotian Zhuang, Xinyi Shang, Wenpin Hou, Zhicheng Ji
Genome Biology 2025
Recommended for multiple use cases in an independent benchmarking study published in Briefings in Bioinformatics.
Identifying cell-type-specific spatially variable genes with ctSVG
Haotian Zhuang, Xinyi Shang, Wenpin Hou, Zhicheng Ji
Genome Biology 2025
Recommended for multiple use cases in an independent benchmarking study published in Briefings in Bioinformatics.
2024
Assessment of treatment effect heterogeneity for multi-regional randomized clinical trials
Haotian Zhuang, Xiaofei Wang, Stephen L. George
Statistics in Biopharmaceutical Research 2024
Assessment of treatment effect heterogeneity for multi-regional randomized clinical trials
Haotian Zhuang, Xiaofei Wang, Stephen L. George
Statistics in Biopharmaceutical Research 2024
2022
findPC: An R package to automatically select the number of principal components in single-cell analysis
Haotian Zhuang, Huimin Wang, Zhicheng Ji
Bioinformatics 2022
findPC: An R package to automatically select the number of principal components in single-cell analysis
Haotian Zhuang, Huimin Wang, Zhicheng Ji
Bioinformatics 2022