273 related articles for article (PubMed ID: 35771600)
21. 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]
22. Single-cell RNA sequencing data analysis based on non-uniform ε-neighborhood network.
Jia J; Chen L
Bioinformatics; 2022 Apr; 38(9):2459-2465. PubMed ID: 35188181
[TBL] [Abstract][Full Text] [Related]
23. Random forest based similarity learning for single cell RNA sequencing data.
Pouyan MB; Kostka D
Bioinformatics; 2018 Jul; 34(13):i79-i88. PubMed ID: 29950006
[TBL] [Abstract][Full Text] [Related]
24. Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.
Haghverdi L; Lun ATL; Morgan MD; Marioni JC
Nat Biotechnol; 2018 Jun; 36(5):421-427. PubMed ID: 29608177
[TBL] [Abstract][Full Text] [Related]
25. CMF-Impute: an accurate imputation tool for single-cell RNA-seq data.
Xu J; Cai L; Liao B; Zhu W; Yang J
Bioinformatics; 2020 May; 36(10):3139-3147. PubMed ID: 32073612
[TBL] [Abstract][Full Text] [Related]
26. FlowGrid enables fast clustering of very large single-cell RNA-seq data.
Fang X; Ho JWK
Bioinformatics; 2021 Dec; 38(1):282-283. PubMed ID: 34289014
[TBL] [Abstract][Full Text] [Related]
27. A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics.
Lakkis J; Wang D; Zhang Y; Hu G; Wang K; Pan H; Ungar L; Reilly MP; Li X; Li M
Genome Res; 2021 Oct; 31(10):1753-1766. PubMed ID: 34035047
[TBL] [Abstract][Full Text] [Related]
28. Spectral clustering based on learning similarity matrix.
Park S; Zhao H
Bioinformatics; 2018 Jun; 34(12):2069-2076. PubMed ID: 29432517
[TBL] [Abstract][Full Text] [Related]
29. GNN-based embedding for clustering scRNA-seq data.
Ciortan M; Defrance M
Bioinformatics; 2022 Jan; 38(4):1037-1044. PubMed ID: 34850828
[TBL] [Abstract][Full Text] [Related]
30. MuDCoD: multi-subject community detection in personalized dynamic gene networks from single-cell RNA sequencing.
Şapcı AOB; Lu S; Yan S; Ay F; Tastan O; Keleş S
Bioinformatics; 2023 Oct; 39(10):. PubMed ID: 37740957
[TBL] [Abstract][Full Text] [Related]
31. EDClust: an EM-MM hybrid method for cell clustering in multiple-subject single-cell RNA sequencing.
Wei X; Li Z; Ji H; Wu H
Bioinformatics; 2022 May; 38(10):2692-2699. PubMed ID: 35561178
[TBL] [Abstract][Full Text] [Related]
32. 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]
33. bayNorm: Bayesian gene expression recovery, imputation and normalization for single-cell RNA-sequencing data.
Tang W; Bertaux F; Thomas P; Stefanelli C; Saint M; Marguerat S; Shahrezaei V
Bioinformatics; 2020 Feb; 36(4):1174-1181. PubMed ID: 31584606
[TBL] [Abstract][Full Text] [Related]
34. scAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data.
Zeng P; Ma Y; Lin Z
Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36383176
[TBL] [Abstract][Full Text] [Related]
35. Deep feature extraction of single-cell transcriptomes by generative adversarial network.
Bahrami M; Maitra M; Nagy C; Turecki G; Rabiee HR; Li Y
Bioinformatics; 2021 Jun; 37(10):1345-1351. PubMed ID: 33226074
[TBL] [Abstract][Full Text] [Related]
36. scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery.
Zhai Y; Chen L; Deng M
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36869836
[TBL] [Abstract][Full Text] [Related]
37. deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors.
Zou B; Zhang T; Zhou R; Jiang X; Yang H; Jin X; Bai Y
Front Genet; 2021; 12():708981. PubMed ID: 34447413
[TBL] [Abstract][Full Text] [Related]
38. CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks.
Buterez D; Bica I; Tariq I; Andrés-Terré H; Liò P
Bioinformatics; 2022 Feb; 38(5):1277-1286. PubMed ID: 34864884
[TBL] [Abstract][Full Text] [Related]
39. Propensity score matching enables batch-effect-corrected imputation in single-cell RNA-seq analysis.
Xu X; Yu X; Hu G; Wang K; Zhang J; Li X
Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35821114
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]