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 *

150 related articles for article (PubMed ID: 25048512)

  • 1. A kernel-based multivariate feature selection method for microarray data classification.
    Sun S; Peng Q; Shakoor A
    PLoS One; 2014; 9(7):e102541. PubMed ID: 25048512
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction.
    Pochet N; De Smet F; Suykens JA; De Moor BL
    Bioinformatics; 2004 Nov; 20(17):3185-95. PubMed ID: 15231531
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data.
    Zhao X; Cheung LW
    BMC Bioinformatics; 2007 Feb; 8():67. PubMed ID: 17328811
    [TBL] [Abstract][Full Text] [Related]  

  • 4. New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.
    Thomas M; De Brabanter K; De Moor B
    BMC Bioinformatics; 2014 May; 15():137. PubMed ID: 24886083
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving PLS-RFE based gene selection for microarray data classification.
    Wang A; An N; Chen G; Li L; Alterovitz G
    Comput Biol Med; 2015 Jul; 62():14-24. PubMed ID: 25912984
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Regularized Least Squares Cancer classifiers from DNA microarray data.
    Ancona N; Maglietta R; D'Addabbo A; Liuni S; Pesole G
    BMC Bioinformatics; 2005 Dec; 6 Suppl 4(Suppl 4):S2. PubMed ID: 16351746
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis.
    Li GZ; Bu HL; Yang MQ; Zeng XQ; Yang JY
    BMC Genomics; 2008 Sep; 9 Suppl 2(Suppl 2):S24. PubMed ID: 18831790
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction.
    Shi P; Ray S; Zhu Q; Kon MA
    BMC Bioinformatics; 2011 Sep; 12():375. PubMed ID: 21939564
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Kernel-based distance metric learning for microarray data classification.
    Xiong H; Chen XW
    BMC Bioinformatics; 2006 Jun; 7():299. PubMed ID: 16774678
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A new regularized least squares support vector regression for gene selection.
    Chen PC; Huang SY; Chen WJ; Hsiao CK
    BMC Bioinformatics; 2009 Feb; 10():44. PubMed ID: 19187562
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Effect of finite sample size on feature selection and classification: a simulation study.
    Way TW; Sahiner B; Hadjiiski LM; Chan HP
    Med Phys; 2010 Feb; 37(2):907-20. PubMed ID: 20229900
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Data-dependent kernel machines for microarray data classification.
    Xiong H; Zhang Y; Chen XW
    IEEE/ACM Trans Comput Biol Bioinform; 2007; 4(4):583-595. PubMed ID: 17975270
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE.
    Niijima S; Kuhara S
    BMC Bioinformatics; 2006 Dec; 7():543. PubMed ID: 17187691
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Feature selection and nearest centroid classification for protein mass spectrometry.
    Levner I
    BMC Bioinformatics; 2005 Mar; 6():68. PubMed ID: 15788095
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genetic algorithm based cancerous gene identification from microarray data using ensemble of filter methods.
    Ghosh M; Adhikary S; Ghosh KK; Sardar A; Begum S; Sarkar R
    Med Biol Eng Comput; 2019 Jan; 57(1):159-176. PubMed ID: 30069674
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A centroid-based gene selection method for microarray data classification.
    Guo S; Guo D; Chen L; Jiang Q
    J Theor Biol; 2016 Jul; 400():32-41. PubMed ID: 27056739
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiers.
    Mavroforakis ME; Georgiou HV; Dimitropoulos N; Cavouras D; Theodoridis S
    Artif Intell Med; 2006 Jun; 37(2):145-62. PubMed ID: 16716579
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Optimal number of features as a function of sample size for various classification rules.
    Hua J; Xiong Z; Lowey J; Suh E; Dougherty ER
    Bioinformatics; 2005 Apr; 21(8):1509-15. PubMed ID: 15572470
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Feature Selection Applied to Microarray Data.
    Alonso-Betanzos A; Bolón-Canedo V; Morán-Fernández L; Seijo-Pardo B
    Methods Mol Biol; 2019; 1986():123-152. PubMed ID: 31115887
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of feature selection and classification for MALDI-MS data.
    Liu Q; Sung AH; Qiao M; Chen Z; Yang JY; Yang MQ; Huang X; Deng Y
    BMC Genomics; 2009 Jul; 10 Suppl 1(Suppl 1):S3. PubMed ID: 19594880
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.