Batch images compression algorithm based on the common features. - Zhiqiong Wang; Zhixiang Lin; Lining Xu; Yue Zhao; Junchang Xin (CISP-BMEI, 2017)

Improved lung nodule diagnosis accuracy using lung CT images with uncertain class. - Zhiqiong Wang; Junchang Xin; Peishun Sun; Zhixiang Lin; Yudong Yao; Xiaosong Gao (Comput. Methods Programs Biomed., 2018)

Elastic Coupled Co-clustering for Single-Cell Genomic Data. - Pengcheng Zeng; Zhixiang Lin (CoRR, 2020)

scAMACE: model-based approach to the joint analysis of single-cell data on chromatin accessibility, gene expression and methylation. - Jiaxuan Wangwu; Zexuan Sun; Zhixiang Lin (Bioinform., 2021)

coupleCoC+: An information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data. - Pengcheng Zeng; Zhixiang Lin (PLoS Comput. Biol., 2021)

JSNMF enables effective and accurate integrative analysis of single-cell multiomics data. - Yuanyuan Ma; Zexuan Sun; Pengcheng Zeng; Wenyu Zhang; Zhixiang Lin (Briefings Bioinform., 2022)

FIRM: Flexible integration of single-cell RNA-sequencing data for large-scale multi-tissue cell atlas datasets. - Jingsi Ming; Zhixiang Lin; Jia Zhao; Xiang Wan; Tabula Microcebus Consortium; Can Yang 002; Angela Ruohao Wu (Briefings Bioinform., 2022)

Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets. - Jia Zhao; Gefei Wang; Jingsi Ming; Zhixiang Lin; Yang Wang; Snigdha Agarwal; Aditi Agrawal; Ahmad Al-Moujahed; Alina Alam; Megan A. Albertelli; Paul Allegakoen; Thomas Ambrosi; et al. (Nat. Comput. Sci., 2022)

RefTM: reference-guided topic modeling of single-cell chromatin accessibility data. - Zheng Zhang; Shengquan Chen; Zhixiang Lin (Briefings Bioinform., 2023)

scAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data. - Pengcheng Zeng; Yuanyuan Ma; Zhixiang Lin (Bioinform., 2023)

stVAE deconvolves cell-type composition in large-scale cellular resolution spatial transcriptomics. - Chen Li; Ting-Fung Chan; Can Yang 002; Zhixiang Lin (Bioinform., 2023)

SGCAST: symmetric graph convolutional auto-encoder for scalable and accurate study of spatial transcriptomics. - Jinzhao Li; Jiong Wang; Zhixiang Lin (Briefings Bioinform., 2024)

scICML: Information-Theoretic Co-Clustering-Based Multi-View Learning for the Integrative Analysis of Single-Cell Multi-Omics Data. - Pengcheng Zeng; Zhixiang Lin (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)