189 related articles for article (PubMed ID: 37815679)
1. Combining Global-Constrained Concept Factorization and a Regularized Gaussian Graphical Model for Clustering Single-Cell RNA-seq Data.
Xu Y; Zhang W; Zheng X; Cai X
Interdiscip Sci; 2024 Mar; 16(1):1-15. PubMed ID: 37815679
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Robust Graph Regularized NMF with Dissimilarity and Similarity Constraints for ScRNA-seq Data Clustering.
Shu Z; Long Q; Zhang L; Yu Z; Wu XJ
J Chem Inf Model; 2022 Dec; 62(23):6271-6286. PubMed ID: 36459053
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. Network-Based Structural Learning Nonnegative Matrix Factorization Algorithm for Clustering of scRNA-Seq Data.
Wu W; Ma X
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(1):566-575. PubMed ID: 35316190
[TBL] [Abstract][Full Text] [Related]
7. Transfer learning for clustering single-cell RNA-seq data crossing-species and batch, case on uterine fibroids.
Wang YM; Sun Y; Wang B; Wu Z; He XY; Zhao Y
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 37991248
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. Single-cell data clustering based on sparse optimization and low-rank matrix factorization.
Hu Y; Li B; Chen F; Qu K
G3 (Bethesda); 2021 Jun; 11(6):. PubMed ID: 33787873
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. 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]
15. 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]
16. A deep matrix factorization based approach for single-cell RNA-seq data clustering.
Liang Z; Zheng R; Chen S; Yan X; Li M
Methods; 2022 Sep; 205():114-122. PubMed ID: 35777719
[TBL] [Abstract][Full Text] [Related]
17. A Gene Rank Based Approach for Single Cell Similarity Assessment and Clustering.
Xu Y; Li HD; Pan Y; Luo F; Wu FX; Wang J
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):431-442. PubMed ID: 31369384
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. An optimized graph-based structure for single-cell RNA-seq cell-type classification based on non-linear dimension reduction.
Abadi SAR; Laghaee SP; Koohi S
BMC Genomics; 2023 May; 24(1):227. PubMed ID: 37127578
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
