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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

120 related articles for article (PubMed ID: 34553226)

  • 1. Consensus-based clustering of single cells by reconstructing cell-to-cell dissimilarity.
    Wang C; Mu Z; Mou C; Zheng H; Liu J
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34553226
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Assessing Dissimilarity Measures for Sample-Based Hierarchical Clustering of RNA Sequencing Data Using Plasmode Datasets.
    Reeb PD; Bramardi SJ; Steibel JP
    PLoS One; 2015; 10(7):e0132310. PubMed ID: 26162080
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Shared Differential Expression-Based Distance Reflects Global Cell Type Relationships in Single-Cell RNA Sequencing Data.
    Mcloughlin A; Huang H
    J Comput Biol; 2022 Aug; 29(8):867-879. PubMed ID: 35793527
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Similarity and Dissimilarity Regularized Nonnegative Matrix Factorization for Single-Cell RNA-seq Analysis.
    Zhu YL; Yuan SS; Liu JX
    Interdiscip Sci; 2022 Mar; 14(1):45-54. PubMed ID: 34231183
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Single-cell RNA-seq data clustering: A survey with performance comparison study.
    Li R; Guan J; Zhou S
    J Bioinform Comput Biol; 2020 Aug; 18(4):2040005. PubMed ID: 32795134
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Single cell RNA-seq data clustering using TF-IDF based methods.
    Moussa M; Măndoiu II
    BMC Genomics; 2018 Aug; 19(Suppl 6):569. PubMed ID: 30367575
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Dimension Reduction and Clustering Models for Single-Cell RNA Sequencing Data: A Comparative Study.
    Feng C; Liu S; Zhang H; Guan R; Li D; Zhou F; Liang Y; Feng X
    Int J Mol Sci; 2020 Mar; 21(6):. PubMed ID: 32235704
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Secuer: Ultrafast, scalable and accurate clustering of single-cell RNA-seq data.
    Wei N; Nie Y; Liu L; Zheng X; Wu HJ
    PLoS Comput Biol; 2022 Dec; 18(12):e1010753. PubMed ID: 36469543
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Effectively Clustering Single Cell RNA Sequencing Data by Sparse Representation.
    Li RY; Wang Z; Guan J; Zhou S
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3425-3434. PubMed ID: 34788219
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Consensus clustering of single-cell RNA-seq data by enhancing network affinity.
    Cui Y; Zhang S; Liang Y; Wang X; Ferraro TN; Chen Y
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34160582
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Dirichlet process mixture models for single-cell RNA-seq clustering.
    Adossa NA; Rytkönen KT; Elo LL
    Biol Open; 2022 Apr; 11(4):. PubMed ID: 35237784
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Clustering and classification methods for single-cell RNA-sequencing data.
    Qi R; Ma A; Ma Q; Zou Q
    Brief Bioinform; 2020 Jul; 21(4):1196-1208. PubMed ID: 31271412
    [TBL] [Abstract][Full Text] [Related]  

  • 18. SUSCC: Secondary Construction of Feature Space based on UMAP for Rapid and Accurate Clustering Large-scale Single Cell RNA-seq Data.
    Wang HY; Zhao JP; Zheng CH
    Interdiscip Sci; 2021 Mar; 13(1):83-90. PubMed ID: 33475958
    [TBL] [Abstract][Full Text] [Related]  

  • 19. KMD clustering: robust general-purpose clustering of biological data.
    Zelig A; Kariti H; Kaplan N
    Commun Biol; 2023 Nov; 6(1):1110. PubMed ID: 37919399
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 6.