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Journal Abstract Search

412 related items for PubMed ID: 15879455

  • 1. Ensemble dependence model for classification and prediction of cancer and normal gene expression data.
    Qiu P, Wang ZJ, Liu KJ.
    Bioinformatics; 2005 Jul 15; 21(14):3114-21. PubMed ID: 15879455
    [Abstract] [Full Text] [Related]

  • 2. Independent component analysis-based penalized discriminant method for tumor classification using gene expression data.
    Huang DS, Zheng CH.
    Bioinformatics; 2006 Aug 01; 22(15):1855-62. PubMed ID: 16709589
    [Abstract] [Full Text] [Related]

  • 3. Structured polychotomous machine diagnosis of multiple cancer types using gene expression.
    Koo JY, Sohn I, Kim S, Lee JW.
    Bioinformatics; 2006 Apr 15; 22(8):950-8. PubMed ID: 16452113
    [Abstract] [Full Text] [Related]

  • 4. Dependence network modeling for biomarker identification.
    Qiu P, Wang ZJ, Liu KJ, Hu ZZ, Wu CH.
    Bioinformatics; 2007 Jan 15; 23(2):198-206. PubMed ID: 17077095
    [Abstract] [Full Text] [Related]

  • 5. Multiclass cancer classification and biomarker discovery using GA-based algorithms.
    Liu JJ, Cutler G, Li W, Pan Z, Peng S, Hoey T, Chen L, Ling XB.
    Bioinformatics; 2005 Jun 01; 21(11):2691-7. PubMed ID: 15814557
    [Abstract] [Full Text] [Related]

  • 6. A combination of rough-based feature selection and RBF neural network for classification using gene expression data.
    Chiang JH, Ho SH.
    IEEE Trans Nanobioscience; 2008 Mar 01; 7(1):91-9. PubMed ID: 18334459
    [Abstract] [Full Text] [Related]

  • 7. Cancer classification and prediction using logistic regression with Bayesian gene selection.
    Zhou X, Liu KY, Wong ST.
    J Biomed Inform; 2004 Aug 01; 37(4):249-59. PubMed ID: 15465478
    [Abstract] [Full Text] [Related]

  • 8. A method for predicting disease subtypes in presence of misclassification among training samples using gene expression: application to human breast cancer.
    Zhang W, Rekaya R, Bertrand K.
    Bioinformatics; 2006 Feb 01; 22(3):317-25. PubMed ID: 16267079
    [Abstract] [Full Text] [Related]

  • 9. Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE.
    Niijima S, Kuhara S.
    BMC Bioinformatics; 2006 Dec 25; 7():543. PubMed ID: 17187691
    [Abstract] [Full Text] [Related]

  • 10. Effects of replacing the unreliable cDNA microarray measurements on the disease classification based on gene expression profiles and functional modules.
    Wang D, Lv Y, Guo Z, Li X, Li Y, Zhu J, Yang D, Xu J, Wang C, Rao S, Yang B.
    Bioinformatics; 2006 Dec 01; 22(23):2883-9. PubMed ID: 16809389
    [Abstract] [Full Text] [Related]

  • 11. Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data.
    Xu L, Tan AC, Naiman DQ, Geman D, Winslow RL.
    Bioinformatics; 2005 Oct 15; 21(20):3905-11. PubMed ID: 16131522
    [Abstract] [Full Text] [Related]

  • 12. Kalman filtering for disease-state estimation from microarray data.
    Kelemen JZ, Kertész-Farkas A, Kocsor A, Puskás LG.
    Bioinformatics; 2006 Dec 15; 22(24):3047-53. PubMed ID: 17065158
    [Abstract] [Full Text] [Related]

  • 13. Biomarker discovery in microarray gene expression data with Gaussian processes.
    Chu W, Ghahramani Z, Falciani F, Wild DL.
    Bioinformatics; 2005 Aug 15; 21(16):3385-93. PubMed ID: 15937031
    [Abstract] [Full Text] [Related]

  • 14. Microarray-based classification and clinical predictors: on combined classifiers and additional predictive value.
    Boulesteix AL, Porzelius C, Daumer M.
    Bioinformatics; 2008 Aug 01; 24(15):1698-706. PubMed ID: 18544547
    [Abstract] [Full Text] [Related]

  • 15. Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data.
    Gui J, Li H.
    Bioinformatics; 2005 Jul 01; 21(13):3001-8. PubMed ID: 15814556
    [Abstract] [Full Text] [Related]

  • 16. Constructing the gene regulation-level representation of microarray data for cancer classification.
    Wong HS, Wang HQ.
    J Biomed Inform; 2008 Feb 01; 41(1):95-105. PubMed ID: 17499026
    [Abstract] [Full Text] [Related]

  • 17. Induction of comprehensible models for gene expression datasets by subgroup discovery methodology.
    Gamberger D, Lavrac N, Zelezný F, Tolar J.
    J Biomed Inform; 2004 Aug 01; 37(4):269-84. PubMed ID: 15465480
    [Abstract] [Full Text] [Related]

  • 18. Detecting common gene expression patterns in multiple cancer outcome entities.
    Yang X, Bentink S, Spang R.
    Biomed Microdevices; 2005 Sep 01; 7(3):247-51. PubMed ID: 16133813
    [Abstract] [Full Text] [Related]

  • 19. Ensemble machine learning on gene expression data for cancer classification.
    Tan AC, Gilbert D.
    Appl Bioinformatics; 2003 Sep 01; 2(3 Suppl):S75-83. PubMed ID: 15130820
    [Abstract] [Full Text] [Related]

  • 20. Improving molecular cancer class discovery through sparse non-negative matrix factorization.
    Gao Y, Church G.
    Bioinformatics; 2005 Nov 01; 21(21):3970-5. PubMed ID: 16244221
    [Abstract] [Full Text] [Related]

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