160 related articles for article (PubMed ID: 34512734)
1. SCDRHA: A scRNA-Seq Data Dimensionality Reduction Algorithm Based on Hierarchical Autoencoder.
Zhao J; Wang N; Wang H; Zheng C; Su Y
Front Genet; 2021; 12():733906. PubMed ID: 34512734
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering.
Zhang T; Ren J; Li L; Wu Z; Zhang Z; Dong G; Wang G
Int J Mol Sci; 2024 May; 25(11):. PubMed ID: 38892162
[TBL] [Abstract][Full Text] [Related]
4. A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis.
Lin E; Mukherjee S; Kannan S
BMC Bioinformatics; 2020 Feb; 21(1):64. PubMed ID: 32085701
[TBL] [Abstract][Full Text] [Related]
5. scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering.
Wang Y; Yu Z; Li S; Bian C; Liang Y; Wong KC; Li X
Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36734596
[TBL] [Abstract][Full Text] [Related]
6. Dimensionality reduction and visualization of single-cell RNA-seq data with an improved deep variational autoencoder.
Jiang J; Xu J; Liu Y; Song B; Guo X; Zeng X; Zou Q
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37088976
[TBL] [Abstract][Full Text] [Related]
7. Attention-based deep clustering method for scRNA-seq cell type identification.
Li S; Guo H; Zhang S; Li Y; Li M
PLoS Comput Biol; 2023 Nov; 19(11):e1011641. PubMed ID: 37948464
[TBL] [Abstract][Full Text] [Related]
8. Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis.
Geddes TA; Kim T; Nan L; Burchfield JG; Yang JYH; Tao D; Yang P
BMC Bioinformatics; 2019 Dec; 20(Suppl 19):660. PubMed ID: 31870278
[TBL] [Abstract][Full Text] [Related]
9. A topology-preserving dimensionality reduction method for single-cell RNA-seq data using graph autoencoder.
Luo Z; Xu C; Zhang Z; Jin W
Sci Rep; 2021 Oct; 11(1):20028. PubMed ID: 34625592
[TBL] [Abstract][Full Text] [Related]
10. scGMAI: a Gaussian mixture model for clustering single-cell RNA-Seq data based on deep autoencoder.
Yu B; Chen C; Qi R; Zheng R; Skillman-Lawrence PJ; Wang X; Ma A; Gu H
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33300547
[TBL] [Abstract][Full Text] [Related]
11. scCDG: A Method Based on DAE and GCN for scRNA-Seq Data Analysis.
Wang HY; Zhao JP; Su YS; Zheng CH
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3685-3694. PubMed ID: 34752401
[TBL] [Abstract][Full Text] [Related]
12. Dimensionality Reduction of Single-Cell RNA Sequencing Data by Combining Entropy and Denoising AutoEncoder.
Zhu X; Li J; Lin Y; Zhao L; Wang J; Peng X
J Comput Biol; 2022 Oct; 29(10):1074-1084. PubMed ID: 35834604
[No Abstract] [Full Text] [Related]
13. VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder.
Wang D; Gu J
Genomics Proteomics Bioinformatics; 2018 Oct; 16(5):320-331. PubMed ID: 30576740
[TBL] [Abstract][Full Text] [Related]
14. Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data.
Su Y; Lin R; Wang J; Tan D; Zheng C
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36715275
[TBL] [Abstract][Full Text] [Related]
15. ScCAEs: deep clustering of single-cell RNA-seq via convolutional autoencoder embedding and soft K-means.
Hu H; Li Z; Li X; Yu M; Pan X
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34472585
[TBL] [Abstract][Full Text] [Related]
16. Contrastive self-supervised clustering of scRNA-seq data.
Ciortan M; Defrance M
BMC Bioinformatics; 2021 May; 22(1):280. PubMed ID: 34044773
[TBL] [Abstract][Full Text] [Related]
17. DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering.
Gao Q; Ai Q
Sci Rep; 2024 Jun; 14(1):13541. PubMed ID: 38866896
[TBL] [Abstract][Full Text] [Related]
18. Multi-View Clustering With Graph Learning for scRNA-Seq Data.
Wu W; Zhang W; Hou W; Ma X
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3535-3546. PubMed ID: 37486829
[TBL] [Abstract][Full Text] [Related]
19. Dual-GCN-based deep clustering with triplet contrast for ScRNA-seq data analysis.
Wang L; Li W; Xie W; Wang R; Yu K
Comput Biol Chem; 2023 Oct; 106():107924. PubMed ID: 37487251
[TBL] [Abstract][Full Text] [Related]
20. scBKAP: A Clustering Model for Single-Cell RNA-Seq Data Based on Bisecting K-Means.
Wang X; Gao H; Qi R; Zheng R; Gao X; Yu B
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(3):2007-2015. PubMed ID: 37015596
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
