BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

160 related articles for article (PubMed ID: 19024496)

  • 1. Sparse p-norm Nonnegative Matrix Factorization for clustering gene expression data.
    Liu W; Yuan K
    Int J Data Min Bioinform; 2008; 2(3):236-49. PubMed ID: 19024496
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Tumor clustering using nonnegative matrix factorization with gene selection.
    Zheng CH; Huang DS; Zhang L; Kong XZ
    IEEE Trans Inf Technol Biomed; 2009 Jul; 13(4):599-607. PubMed ID: 19369170
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Improving molecular cancer class discovery through sparse non-negative matrix factorization.
    Gao Y; Church G
    Bioinformatics; 2005 Nov; 21(21):3970-5. PubMed ID: 16244221
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Cancer molecular pattern discovery by subspace consensus kernel classification.
    Han X
    Comput Syst Bioinformatics Conf; 2007; 6():55-65. PubMed ID: 17951812
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Hessian regularization based symmetric nonnegative matrix factorization for clustering gene expression and microbiome data.
    Ma Y; Hu X; He T; Jiang X
    Methods; 2016 Dec; 111():80-84. PubMed ID: 27339941
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Robust Manifold Graph Regularized Nonnegative Matrix Factorization Algorithm for Cancer Gene Clustering.
    Zhu R; Liu JX; Zhang YK; Guo Y
    Molecules; 2017 Dec; 22(12):. PubMed ID: 29207477
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Impact of the Choice of Normalization Method on Molecular Cancer Class Discovery Using Nonnegative Matrix Factorization.
    Yang H; Seoighe C
    PLoS One; 2016; 11(10):e0164880. PubMed ID: 27741311
    [TBL] [Abstract][Full Text] [Related]  

  • 8. On alpha-divergence based nonnegative matrix factorization for clustering cancer gene expression data.
    Liu W; Yuan K; Ye D
    Artif Intell Med; 2008 Sep; 44(1):1-5. PubMed ID: 18602254
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Non-negative matrix factorization by maximizing correntropy for cancer clustering.
    Wang JJ; Wang X; Gao X
    BMC Bioinformatics; 2013 Mar; 14():107. PubMed ID: 23522344
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Reducing microarray data via nonnegative matrix factorization for visualization and clustering analysis.
    Liu W; Yuan K; Ye D
    J Biomed Inform; 2008 Aug; 41(4):602-6. PubMed ID: 18234564
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Data representation using robust nonnegative matrix factorization for edge computing.
    Yang Q; Chen J; Al-Nabhan N
    Math Biosci Eng; 2022 Jan; 19(2):2147-2178. PubMed ID: 35135245
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Metagenes and molecular pattern discovery using matrix factorization.
    Brunet JP; Tamayo P; Golub TR; Mesirov JP
    Proc Natl Acad Sci U S A; 2004 Mar; 101(12):4164-9. PubMed ID: 15016911
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Convex nonnegative matrix factorization with manifold regularization.
    Hu W; Choi KS; Wang P; Jiang Y; Wang S
    Neural Netw; 2015 Mar; 63():94-103. PubMed ID: 25523040
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Mixed-Norm Laplacian Regularized Low-Rank Representation Method for Tumor Samples Clustering.
    Wang J; Liu JX; Zheng CH; Wang YX; Kong XZ; Wen CG
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(1):172-182. PubMed ID: 29990217
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Nonnegative local coordinate factorization for image representation.
    Chen Y; Zhang J; Cai D; Liu W; He X
    IEEE Trans Image Process; 2013 Mar; 22(3):969-79. PubMed ID: 23076045
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Nonnegative Matrix Factorization with Rank Regularization and Hard Constraint.
    Shang R; Liu C; Meng Y; Jiao L; Stolkin R
    Neural Comput; 2017 Sep; 29(9):2553-2579. PubMed ID: 28777717
    [TBL] [Abstract][Full Text] [Related]  

  • 17. An effective fuzzy kernel clustering analysis approach for gene expression data.
    Sun L; Xu J; Yin J
    Biomed Mater Eng; 2015; 26 Suppl 1():S1863-9. PubMed ID: 26405958
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey.
    Liu JX; Wang D; Gao YL; Zheng CH; Xu Y; Yu J
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(3):974-987. PubMed ID: 28186906
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Blind spectral unmixing based on sparse nonnegative matrix factorization.
    Yang Z; Zhou G; Xie S; Ding S; Yang JM; Zhang J
    IEEE Trans Image Process; 2011 Apr; 20(4):1112-25. PubMed ID: 20889432
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A practical comparison of two K-Means clustering algorithms.
    Wilkin GA; Huang X
    BMC Bioinformatics; 2008 May; 9 Suppl 6(Suppl 6):S19. PubMed ID: 18541054
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.