The following publications are possibly variants of this publication:
- AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identificationXiaoshu Zhu, Shuang Meng, Gaoshi Li, Jian-xin Wang 0001, Xiaoqing Peng. bioinformatics, 40(2), February 2024. [doi]
- scGCL: an imputation method for scRNA-seq data based on graph contrastive learningZehao Xiong, Jiawei Luo 0001, Wanwan Shi, Ying Liu, Zhongyuan Xu, Bo Wang. bioinformatics, 39(3), March 2023. [doi]
- Matrix factorization for biomedical link prediction and scRNA-seq data imputation: an empirical surveyLe Ou-Yang, Fan Lu, Zi-Chao Zhang, Min Wu 0008. bib, 23(1), 2022. [doi]
- Are dropout imputation methods for scRNA-seq effective for scATAC-seq data?Yue Liu, Junfeng Zhang, Shu-Lin Wang, Xiangxiang Zeng, Wei Zhang 0089. bib, 23(1), 2022. [doi]