These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
2. 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]
3. scAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data. Zeng P; Ma Y; Lin Z Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36383176 [TBL] [Abstract][Full Text] [Related]
4. scCNC: a method based on capsule network for clustering scRNA-seq data. Wang HY; Zhao JP; Zheng CH; Su YS Bioinformatics; 2022 Aug; 38(15):3703-3709. PubMed ID: 35699473 [TBL] [Abstract][Full Text] [Related]
5. Spectral clustering based on learning similarity matrix. Park S; Zhao H Bioinformatics; 2018 Jun; 34(12):2069-2076. PubMed ID: 29432517 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. Impact of similarity metrics on single-cell RNA-seq data clustering. Kim T; Chen IR; Lin Y; Wang AY; Yang JYH; Yang P Brief Bioinform; 2019 Nov; 20(6):2316-2326. PubMed ID: 30137247 [TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge. Mukherjee S; Zhang Y; Fan J; Seelig G; Kannan S Bioinformatics; 2018 Jul; 34(13):i124-i132. PubMed ID: 29949988 [TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. 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]
15. scSTEM: clustering pseudotime ordered single-cell data. Song Q; Wang J; Bar-Joseph Z Genome Biol; 2022 Jul; 23(1):150. PubMed ID: 35799304 [TBL] [Abstract][Full Text] [Related]
16. A clustering method for small scRNA-seq data based on subspace and weighted distance. Ning Z; Dai Z; Zhang H; Chen Y; Yuan Z PeerJ; 2023; 11():e14706. PubMed ID: 36710872 [TBL] [Abstract][Full Text] [Related]
17. Random forest based similarity learning for single cell RNA sequencing data. Pouyan MB; Kostka D Bioinformatics; 2018 Jul; 34(13):i79-i88. PubMed ID: 29950006 [TBL] [Abstract][Full Text] [Related]
18. SSRE: Cell Type Detection Based on Sparse Subspace Representation and Similarity Enhancement. Liang Z; Li M; Zheng R; Tian Y; Yan X; Chen J; Wu FX; Wang J Genomics Proteomics Bioinformatics; 2021 Apr; 19(2):282-291. PubMed ID: 33647482 [TBL] [Abstract][Full Text] [Related]
19. How does the structure of data impact cell-cell similarity? Evaluating how structural properties influence the performance of proximity metrics in single cell RNA-seq data. Watson ER; Mora A; Taherian Fard A; Mar JC Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36151725 [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]