BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

265 related articles for article (PubMed ID: 37751336)

  • 1. scGCC: Graph Contrastive Clustering With Neighborhood Augmentations for scRNA-Seq Data Analysis.
    Tian SW; Ni JC; Wang YT; Zheng CH; Ji CM
    IEEE J Biomed Health Inform; 2023 Dec; 27(12):6133-6143. PubMed ID: 37751336
    [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. 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]  

  • 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. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. CL-Impute: A contrastive learning-based imputation for dropout single-cell RNA-seq data.
    Shi Y; Wan J; Zhang X; Yin Y
    Comput Biol Med; 2023 Sep; 164():107263. PubMed ID: 37531858
    [TBL] [Abstract][Full Text] [Related]  

  • 10. scGCL: an imputation method for scRNA-seq data based on graph contrastive learning.
    Xiong Z; Luo J; Shi W; Liu Y; Xu Z; Wang B
    Bioinformatics; 2023 Mar; 39(3):. PubMed ID: 36825817
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.
    Gan Y; Huang X; Zou G; Zhou S; Guan J
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35172334
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. 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]  

  • 14. 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]  

  • 15. 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]  

  • 16. ScCCL: Single-Cell Data Clustering Based on Self-Supervised Contrastive Learning.
    Du L; Han R; Liu B; Wang Y; Li J
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(3):2233-2241. PubMed ID: 37022258
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. 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]  

  • 19. 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]  

  • 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]
    of 14.