770 related articles for article (PubMed ID: 34999761)
1. scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq data.
Wan H; Chen L; Deng M
Bioinformatics; 2022 Mar; 38(6):1575-1583. PubMed ID: 34999761
[TBL] [Abstract][Full Text] [Related]
2. Deep enhanced constraint clustering based on contrastive learning for scRNA-seq data.
Gan Y; Chen Y; Xu G; Guo W; Zou G
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37313714
[TBL] [Abstract][Full Text] [Related]
3. scDCCA: deep contrastive clustering for single-cell RNA-seq data based on auto-encoder network.
Wang J; Xia J; Wang H; Su Y; Zheng CH
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36631401
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. scGCC: Graph Contrastive Clustering With Neighborhood Augmentations for scRNA-Seq Data Analysis.
Tian SW; Ni JC; Wang YT; Zheng CH; Ji CM
IEEE J Biomed Health Inform; 2023 Dec; 27(12):6133-6143. PubMed ID: 37751336
[TBL] [Abstract][Full Text] [Related]
6. A Personalized Low-Rank Subspace Clustering Method Based on Locality and Similarity Constraints for scRNA-seq Data Analysis.
Qiao TJ; Liu JX; Shang J; Yuan S; Zheng CH; Wang J
IEEE J Biomed Health Inform; 2023 May; 27(5):2575-2584. PubMed ID: 37027680
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. 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]
10. Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning.
Lee J; Kim S; Hyun D; Lee N; Kim Y; Park C
Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37233193
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data.
Qiu Y; Yan C; Zhao P; Zou Q
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37122068
[TBL] [Abstract][Full Text] [Related]
13. scNCL: transferring labels from scRNA-seq to scATAC-seq data with neighborhood contrastive regularization.
Yan X; Zheng R; Chen J; Li M
Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37584660
[TBL] [Abstract][Full Text] [Related]
14. JLONMFSC: Clustering scRNA-seq data based on joint learning of non-negative matrix factorization and subspace clustering.
Lan W; Liu M; Chen J; Ye J; Zheng R; Zhu X; Peng W
Methods; 2024 Feb; 222():1-9. PubMed ID: 38128706
[TBL] [Abstract][Full Text] [Related]
15. 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]
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. Self-supervised deep clustering of single-cell RNA-seq data to hierarchically detect rare cell populations.
Lei T; Chen R; Zhang S; Chen Y
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37769630
[TBL] [Abstract][Full Text] [Related]
18. scHFC: a hybrid fuzzy clustering method for single-cell RNA-seq data optimized by natural computation.
Wang J; Xia J; Tan D; Lin R; Su Y; Zheng CH
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35136924
[TBL] [Abstract][Full Text] [Related]
19. scTPC: a novel semisupervised deep clustering model for scRNA-seq data.
Qiu Y; Yang L; Jiang H; Zou Q
Bioinformatics; 2024 May; 40(5):. PubMed ID: 38684178
[TBL] [Abstract][Full Text] [Related]
20. scGAC: a graph attentional architecture for clustering single-cell RNA-seq data.
Cheng Y; Ma X
Bioinformatics; 2022 Apr; 38(8):2187-2193. PubMed ID: 35176138
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
