176 related articles for article (PubMed ID: 37185897)
1. A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection.
Mallick K; Chakraborty S; Mallik S; Bandyopadhyay S
Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37185897
[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. 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]
4. 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]
5. 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]
6. scASGC: An adaptive simplified graph convolution model for clustering single-cell RNA-seq data.
Wang S; Zhang Y; Zhang Y; Wu W; Ye L; Li Y; Su J; Pang S
Comput Biol Med; 2023 Sep; 163():107152. PubMed ID: 37364529
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. 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]
10. CTEC: a cross-tabulation ensemble clustering approach for single-cell RNA sequencing data analysis.
Wang L; Hong C; Song J; Yao J
Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38552307
[TBL] [Abstract][Full Text] [Related]
11. Evaluation of single-cell RNAseq labelling algorithms using cancer datasets.
Christensen E; Luo P; Turinsky A; Husić M; Mahalanabis A; Naidas A; Diaz-Mejia JJ; Brudno M; Pugh T; Ramani A; Shooshtari P
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36585784
[TBL] [Abstract][Full Text] [Related]
12. Machine learning and statistical methods for clustering single-cell RNA-sequencing data.
Petegrosso R; Li Z; Kuang R
Brief Bioinform; 2020 Jul; 21(4):1209-1223. PubMed ID: 31243426
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. 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]
16. 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]
17. scDFC: A deep fusion clustering method for single-cell RNA-seq data.
Hu D; Liang K; Zhou S; Tu W; Liu M; Liu X
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37280190
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. scMAE: a masked autoencoder for single-cell RNA-seq clustering.
Fang Z; Zheng R; Li M
Bioinformatics; 2024 Jan; 40(1):. PubMed ID: 38230824
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]