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 *

157 related articles for article (PubMed ID: 34096998)

  • 1. HGC: fast hierarchical clustering for large-scale single-cell data.
    Zou Z; Hua K; Zhang X
    Bioinformatics; 2021 Nov; 37(21):3964-3965. PubMed ID: 34096998
    [TBL] [Abstract][Full Text] [Related]  

  • 2. GMHCC: high-throughput analysis of biomolecular data using graph-based multiple hierarchical consensus clustering.
    Lu Y; Yu Z; Wang Y; Ma Z; Wong KC; Li X
    Bioinformatics; 2022 May; 38(11):3020-3028. PubMed ID: 35451457
    [TBL] [Abstract][Full Text] [Related]  

  • 3. densityCut: an efficient and versatile topological approach for automatic clustering of biological data.
    Ding J; Shah S; Condon A
    Bioinformatics; 2016 Sep; 32(17):2567-76. PubMed ID: 27153661
    [TBL] [Abstract][Full Text] [Related]  

  • 4. clustComp, a bioconductor package for the comparison of clustering results.
    Torrente A; Brazma A
    Bioinformatics; 2017 Dec; 33(24):4001-4003. PubMed ID: 28961761
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SCHNEL: scalable clustering of high dimensional single-cell data.
    Abdelaal T; de Raadt P; Lelieveldt BPF; Reinders MJT; Mahfouz A
    Bioinformatics; 2020 Dec; 36(Suppl_2):i849-i856. PubMed ID: 33381821
    [TBL] [Abstract][Full Text] [Related]  

  • 6. TreeAndLeaf: an R/Bioconductor package for graphs and trees with focus on the leaves.
    Cardoso MA; Rizzardi LEA; Kume LW; Groeneveld CS; Trefflich S; Morais DAA; Dalmolin RJS; Ponder BAJ; Meyer KB; Castro MAA
    Bioinformatics; 2022 Feb; 38(5):1463-1464. PubMed ID: 34864914
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Single-Cell Clustering Based on Shared Nearest Neighbor and Graph Partitioning.
    Zhu X; Zhang J; Xu Y; Wang J; Peng X; Li HD
    Interdiscip Sci; 2020 Jun; 12(2):117-130. PubMed ID: 32086753
    [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. 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]  

  • 11. Bipartite graph-based approach for clustering of cell lines by gene expression-drug response associations.
    Chi C; Ye Y; Chen B; Huang H
    Bioinformatics; 2021 Sep; 37(17):2617-2626. PubMed ID: 33682877
    [TBL] [Abstract][Full Text] [Related]  

  • 12. PARC: ultrafast and accurate clustering of phenotypic data of millions of single cells.
    Stassen SV; Siu DMD; Lee KCM; Ho JWK; So HKH; Tsia KK
    Bioinformatics; 2020 May; 36(9):2778-2786. PubMed ID: 31971583
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Single cell clustering based on cell-pair differentiability correlation and variance analysis.
    Jiang H; Sohn LL; Huang H; Chen L
    Bioinformatics; 2018 Nov; 34(21):3684-3694. PubMed ID: 29771290
    [TBL] [Abstract][Full Text] [Related]  

  • 14. HCsnip: An R Package for Semi-supervised Snipping of the Hierarchical Clustering Tree.
    Obulkasim A; van de Wiel MA
    Cancer Inform; 2015; 14():1-19. PubMed ID: 25861213
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A dynamically growing self-organizing tree (DGSOT) for hierarchical clustering gene expression profiles.
    Luo F; Khan L; Bastani F; Yen IL; Zhou J
    Bioinformatics; 2004 Nov; 20(16):2605-17. PubMed ID: 15130935
    [TBL] [Abstract][Full Text] [Related]  

  • 16. benchdamic: benchmarking of differential abundance methods for microbiome data.
    Calgaro M; Romualdi C; Risso D; Vitulo N
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36477500
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Semi-supervised adaptive-height snipping of the hierarchical clustering tree.
    Obulkasim A; Meijer GA; van de Wiel MA
    BMC Bioinformatics; 2015 Jan; 16(1):15. PubMed ID: 25592847
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Spectrum: fast density-aware spectral clustering for single and multi-omic data.
    John CR; Watson D; Barnes MR; Pitzalis C; Lewis MJ
    Bioinformatics; 2020 Feb; 36(4):1159-1166. PubMed ID: 31501851
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq.
    Juliá M; Telenti A; Rausell A
    Bioinformatics; 2015 Oct; 31(20):3380-2. PubMed ID: 26099264
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.