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Journal Abstract Search

170 related items for PubMed ID: 18334457

  • 1. Investigation of self-organizing oscillator networks for use in clustering microarray data.
    Salem SA, Jack LB, Nandi AK.
    IEEE Trans Nanobioscience; 2008 Mar; 7(1):65-79. PubMed ID: 18334457
    [Abstract] [Full Text] [Related]

  • 2. Class discovery from gene expression data based on perturbation and cluster ensemble.
    Yu Z, Wong HS.
    IEEE Trans Nanobioscience; 2009 Jun; 8(2):147-60. PubMed ID: 19497836
    [Abstract] [Full Text] [Related]

  • 3. Markers improve clustering of CGH data.
    Liu J, Ranka S, Kahveci T.
    Bioinformatics; 2007 Feb 15; 23(4):450-7. PubMed ID: 17150994
    [Abstract] [Full Text] [Related]

  • 4. 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]

  • 5. Graph-based consensus clustering for class discovery from gene expression data.
    Yu Z, Wong HS, Wang H.
    Bioinformatics; 2007 Nov 01; 23(21):2888-96. PubMed ID: 17872912
    [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. Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.
    Cawley GC, Talbot NL.
    Bioinformatics; 2006 Oct 01; 22(19):2348-55. PubMed ID: 16844704
    [Abstract] [Full Text] [Related]

  • 8. Annotation-based distance measures for patient subgroup discovery in clinical microarray studies.
    Lottaz C, Toedling J, Spang R.
    Bioinformatics; 2007 Sep 01; 23(17):2256-64. PubMed ID: 17586546
    [Abstract] [Full Text] [Related]

  • 9. Clustering threshold gradient descent regularization: with applications to microarray studies.
    Ma S, Huang J.
    Bioinformatics; 2007 Feb 15; 23(4):466-72. PubMed ID: 17182700
    [Abstract] [Full Text] [Related]

  • 10. 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]

  • 11. A simple and robust algorithm for microarray data clustering based on gene population-variance ratio metric.
    Chatterjee S, Bhattacharjee K, Konar A.
    Biotechnol J; 2009 Sep 15; 4(9):1357-61. PubMed ID: 19579218
    [Abstract] [Full Text] [Related]

  • 12. Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm.
    Grotkjaer T, Winther O, Regenberg B, Nielsen J, Hansen LK.
    Bioinformatics; 2006 Jan 01; 22(1):58-67. PubMed ID: 16257984
    [Abstract] [Full Text] [Related]

  • 13. 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]

  • 14. FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis.
    Liang LR, Lu S, Wang X, Lu Y, Mandal V, Patacsil D, Kumar D.
    BMC Bioinformatics; 2006 Dec 12; 7 Suppl 4(Suppl 4):S7. PubMed ID: 17217525
    [Abstract] [Full Text] [Related]

  • 15. A method for clustering gene expression data based on graph structure.
    Seno S, Teramoto R, Takenaka Y, Matsuda H.
    Genome Inform; 2004 Dec 12; 15(2):151-60. PubMed ID: 15706501
    [Abstract] [Full Text] [Related]

  • 16. Clustering of change patterns using Fourier coefficients.
    Kim J, Kim H.
    Bioinformatics; 2008 Jan 15; 24(2):184-91. PubMed ID: 18025003
    [Abstract] [Full Text] [Related]

  • 17. Detecting biological associations between genes based on the theory of phase synchronization.
    Kim CS, Riikonen P, Salakoski T.
    Biosystems; 2008 May 15; 92(2):99-113. PubMed ID: 18289772
    [Abstract] [Full Text] [Related]

  • 18. Analysis of a Gibbs sampler method for model-based clustering of gene expression data.
    Joshi A, Van de Peer Y, Michoel T.
    Bioinformatics; 2008 Jan 15; 24(2):176-83. PubMed ID: 18033794
    [Abstract] [Full Text] [Related]

  • 19. CLUM: a cluster program for analyzing microarray data.
    Irigoien I, Fernandez E, Vives S, Arenas C.
    Genetika; 2008 Aug 15; 44(8):1137-40. PubMed ID: 18825964
    [Abstract] [Full Text] [Related]

  • 20. Techniques for clustering gene expression data.
    Kerr G, Ruskin HJ, Crane M, Doolan P.
    Comput Biol Med; 2008 Mar 15; 38(3):283-93. PubMed ID: 18061589
    [Abstract] [Full Text] [Related]

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