577 related articles for article (PubMed ID: 36733262)
1. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network.
Huang Z; Wang J; Lu X; Mohd Zain A; Yu G
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36733262
[TBL] [Abstract][Full Text] [Related]
2. GE-Impute: graph embedding-based imputation for single-cell RNA-seq data.
Wu X; Zhou Y
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35901457
[TBL] [Abstract][Full Text] [Related]
3. CL-Impute: A contrastive learning-based imputation for dropout single-cell RNA-seq data.
Shi Y; Wan J; Zhang X; Yin Y
Comput Biol Med; 2023 Sep; 164():107263. PubMed ID: 37531858
[TBL] [Abstract][Full Text] [Related]
4. A novel f-divergence based generative adversarial imputation method for scRNA-seq data analysis.
Si T; Hopkins Z; Yanev J; Hou J; Gong H
PLoS One; 2023; 18(11):e0292792. PubMed ID: 37948433
[TBL] [Abstract][Full Text] [Related]
5. Bubble: a fast single-cell RNA-seq imputation using an autoencoder constrained by bulk RNA-seq data.
Chen S; Yan X; Zheng R; Li M
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36567258
[TBL] [Abstract][Full Text] [Related]
6. scGCL: an imputation method for scRNA-seq data based on graph contrastive learning.
Xiong Z; Luo J; Shi W; Liu Y; Xu Z; Wang B
Bioinformatics; 2023 Mar; 39(3):. PubMed ID: 36825817
[TBL] [Abstract][Full Text] [Related]
7. AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification.
Zhu X; Meng S; Li G; Wang J; Peng X
Bioinformatics; 2024 Feb; 40(2):. PubMed ID: 38317025
[TBL] [Abstract][Full Text] [Related]
8. scMultiGAN: cell-specific imputation for single-cell transcriptomes with multiple deep generative adversarial networks.
Wang T; Zhao H; Xu Y; Wang Y; Shang X; Peng J; Xiao B
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37903416
[TBL] [Abstract][Full Text] [Related]
9. A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data.
Qi Y; Guo Y; Jiao H; Shang X
BMC Bioinformatics; 2020 Jun; 21(1):240. PubMed ID: 32527285
[TBL] [Abstract][Full Text] [Related]
10. Accurate and interpretable gene expression imputation on scRNA-seq data using IGSimpute.
Xu K; Cheong C; Veldsman WP; Lyu A; Cheung WK; Zhang L
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37039664
[TBL] [Abstract][Full Text] [Related]
11. Improvements Achieved by Multiple Imputation for Single-Cell RNA-Seq Data in Clustering Analysis and Differential Expression Analysis.
Zhu M; Lai Y
J Comput Biol; 2022 Jul; 29(7):634-649. PubMed ID: 35575729
[TBL] [Abstract][Full Text] [Related]
12. Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq.
Raevskiy M; Yanvarev V; Jung S; Del Sol A; Medvedeva YA
Int J Mol Sci; 2023 Mar; 24(7):. PubMed ID: 37047200
[TBL] [Abstract][Full Text] [Related]
13. A posterior probability based Bayesian method for single-cell RNA-seq data imputation.
Chen S; Zheng R; Tian L; Wu FX; Li M
Methods; 2023 Aug; 216():21-38. PubMed ID: 37315825
[TBL] [Abstract][Full Text] [Related]
14. scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data.
Ye W; Ji G; Ye P; Long Y; Xiao X; Li S; Su Y; Wu X
BMC Genomics; 2019 May; 20(1):347. PubMed ID: 31068142
[TBL] [Abstract][Full Text] [Related]
15. scIGANs: single-cell RNA-seq imputation using generative adversarial networks.
Xu Y; Zhang Z; You L; Liu J; Fan Z; Zhou X
Nucleic Acids Res; 2020 Sep; 48(15):e85. PubMed ID: 32588900
[TBL] [Abstract][Full Text] [Related]
16. Learning deep features and topological structure of cells for clustering of scRNA-sequencing data.
Wang H; Ma X
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35302164
[TBL] [Abstract][Full Text] [Related]
17. Single-cell RNA-seq data analysis based on directed graph neural network.
Feng X; Zhang H; Lin H; Long H
Methods; 2023 Mar; 211():48-60. PubMed ID: 36804214
[TBL] [Abstract][Full Text] [Related]
18. Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks.
Mao G; Pang Z; Zuo K; Wang Q; Pei X; Chen X; Liu J
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37985457
[TBL] [Abstract][Full Text] [Related]
19. scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data.
Wang Z; Wang H; Zhao J; Zheng C
BMC Bioinformatics; 2023 May; 24(1):217. PubMed ID: 37237310
[TBL] [Abstract][Full Text] [Related]
20. Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.
Gan Y; Huang X; Zou G; Zhou S; Guan J
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35172334
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]