254 related articles for article (PubMed ID: 33285568)
1. FEATS: feature selection-based clustering of single-cell RNA-seq data.
Vans E; Patil A; Sharma A
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33285568
[TBL] [Abstract][Full Text] [Related]
2. SAFE-clustering: Single-cell Aggregated (from Ensemble) clustering for single-cell RNA-seq data.
Yang Y; Huh R; Culpepper HW; Lin Y; Love MI; Li Y
Bioinformatics; 2019 Apr; 35(8):1269-1277. PubMed ID: 30202935
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. scGNN 2.0: a graph neural network tool for imputation and clustering of single-cell RNA-Seq data.
Gu H; Cheng H; Ma A; Li Y; Wang J; Xu D; Ma Q
Bioinformatics; 2022 Nov; 38(23):5322-5325. PubMed ID: 36250784
[TBL] [Abstract][Full Text] [Related]
5. Coupled co-clustering-based unsupervised transfer learning for the integrative analysis of single-cell genomic data.
Zeng P; Wangwu J; Lin Z
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33279962
[TBL] [Abstract][Full Text] [Related]
6. An interpretable framework for clustering single-cell RNA-Seq datasets.
Zhang JM; Fan J; Fan HC; Rosenfeld D; Tse DN
BMC Bioinformatics; 2018 Mar; 19(1):93. PubMed ID: 29523077
[TBL] [Abstract][Full Text] [Related]
7. Joint learning dimension reduction and clustering of single-cell RNA-sequencing data.
Wu W; Ma X
Bioinformatics; 2020 Jun; 36(12):3825-3832. PubMed ID: 32246821
[TBL] [Abstract][Full Text] [Related]
8. Improving Single-Cell RNA-seq Clustering by Integrating Pathways.
Zhang C; Gao L; Wang B; Gao Y
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 33940590
[TBL] [Abstract][Full Text] [Related]
9. DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.
Sun Z; Wang T; Deng K; Wang XF; Lafyatis R; Ding Y; Hu M; Chen W
Bioinformatics; 2018 Jan; 34(1):139-146. PubMed ID: 29036318
[TBL] [Abstract][Full Text] [Related]
10. coupleCoC+: An information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data.
Zeng P; Lin Z
PLoS Comput Biol; 2021 Jun; 17(6):e1009064. PubMed ID: 34077420
[TBL] [Abstract][Full Text] [Related]
11. Single-cell RNA-seq interpretations using evolutionary multiobjective ensemble pruning.
Li X; Zhang S; Wong KC
Bioinformatics; 2019 Aug; 35(16):2809-2817. PubMed ID: 30596898
[TBL] [Abstract][Full Text] [Related]
12. scEFSC: Accurate single-cell RNA-seq data analysis via ensemble consensus clustering based on multiple feature selections.
Bian C; Wang X; Su Y; Wang Y; Wong KC; Li X
Comput Struct Biotechnol J; 2022; 20():2181-2197. PubMed ID: 35615016
[TBL] [Abstract][Full Text] [Related]
13. A spectral clustering with self-weighted multiple kernel learning method for single-cell RNA-seq data.
Qi R; Wu J; Guo F; Xu L; Zou Q
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33003206
[TBL] [Abstract][Full Text] [Related]
14. FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test.
Zhang Y; Aevermann BD; Bakken TE; Miller JA; Hodge RD; Lein ES; Scheuermann RH
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33249453
[TBL] [Abstract][Full Text] [Related]
15. Single-cell RNA-seq data semi-supervised clustering and annotation via structural regularized domain adaptation.
Chen L; He Q; Zhai Y; Deng M
Bioinformatics; 2021 May; 37(6):775-784. PubMed ID: 33098418
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. FBA: feature barcoding analysis for single cell RNA-Seq.
Duan J; Hon GC
Bioinformatics; 2021 Nov; 37(22):4266-4268. PubMed ID: 33999185
[TBL] [Abstract][Full Text] [Related]
18. SSCC: A Novel Computational Framework for Rapid and Accurate Clustering Large-scale Single Cell RNA-seq Data.
Ren X; Zheng L; Zhang Z
Genomics Proteomics Bioinformatics; 2019 Apr; 17(2):201-210. PubMed ID: 31202000
[TBL] [Abstract][Full Text] [Related]
19. Accurate feature selection improves single-cell RNA-seq cell clustering.
Su K; Yu T; Wu H
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33611426
[TBL] [Abstract][Full Text] [Related]
20. scAce: an adaptive embedding and clustering method for single-cell gene expression data.
He X; Qian K; Wang Z; Zeng S; Li H; Li WV
Bioinformatics; 2023 Sep; 39(9):. PubMed ID: 37672035
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]