350 related articles for article (PubMed ID: 34244616)
1. An active learning approach for clustering single-cell RNA-seq data.
Lin X; Liu H; Wei Z; Roy SB; Gao N
Lab Invest; 2022 Mar; 102(3):227-235. PubMed ID: 34244616
[TBL] [Abstract][Full Text] [Related]
2. Integrating Deep Supervised, Self-Supervised and Unsupervised Learning for Single-Cell RNA-seq Clustering and Annotation.
Chen L; Zhai Y; He Q; Wang W; Deng M
Genes (Basel); 2020 Jul; 11(7):. PubMed ID: 32674393
[TBL] [Abstract][Full Text] [Related]
3. A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data.
Srinivasan S; Leshchyk A; Johnson NT; Korkin D
RNA; 2020 Oct; 26(10):1303-1319. PubMed ID: 32532794
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.
Zhang H; Lee CAA; Li Z; Garbe JR; Eide CR; Petegrosso R; Kuang R; Tolar J
PLoS Comput Biol; 2018 Apr; 14(4):e1006053. PubMed ID: 29630593
[TBL] [Abstract][Full Text] [Related]
7. jSRC: a flexible and accurate joint learning algorithm for clustering of single-cell RNA-sequencing data.
Wu W; Liu Z; Ma X
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33535230
[TBL] [Abstract][Full Text] [Related]
8. scDSSC: Deep Sparse Subspace Clustering for scRNA-seq Data.
Wang H; Zhao J; Zheng C; Su Y
PLoS Comput Biol; 2022 Dec; 18(12):e1010772. PubMed ID: 36534702
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. 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]
12. Identifying cell types to interpret scRNA-seq data: how, why and more possibilities.
Wang Z; Ding H; Zou Q
Brief Funct Genomics; 2020 Jul; 19(4):286-291. PubMed ID: 32232401
[TBL] [Abstract][Full Text] [Related]
13. Deep embedded clustering with multiple objectives on scRNA-seq data.
Li X; Zhang S; Wong KC
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33822877
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. 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]
17. ScGSLC: An unsupervised graph similarity learning framework for single-cell RNA-seq data clustering.
Li J; Jiang W; Han H; Liu J; Liu B; Wang Y
Comput Biol Chem; 2021 Feb; 90():107415. PubMed ID: 33307360
[TBL] [Abstract][Full Text] [Related]
18. Single-cell RNA-sequencing data clustering using variational graph attention auto-encoder with self-supervised leaning.
Li B; Peng C; You Z; Zhang X; Zhang S
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37898127
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. 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]
[Next] [New Search]