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Journal Abstract Search

219 related items for PubMed ID: 20802251

  • 21. Knowledge guided analysis of microarray data.
    Fang Z, Yang J, Li Y, Luo Q, Liu L.
    J Biomed Inform; 2006 Aug; 39(4):401-11. PubMed ID: 16214421
    [Abstract] [Full Text] [Related]

  • 22. Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach.
    Pihur V, Datta S, Datta S.
    Bioinformatics; 2007 Jul 01; 23(13):1607-15. PubMed ID: 17483500
    [Abstract] [Full Text] [Related]

  • 23. 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 01; 4(9):1357-61. PubMed ID: 19579218
    [Abstract] [Full Text] [Related]

  • 24. goCluster integrates statistical analysis and functional interpretation of microarray expression data.
    Wrobel G, Chalmel F, Primig M.
    Bioinformatics; 2005 Sep 01; 21(17):3575-7. PubMed ID: 16020468
    [Abstract] [Full Text] [Related]

  • 25. How does gene expression clustering work?
    D'haeseleer P.
    Nat Biotechnol; 2005 Dec 01; 23(12):1499-501. PubMed ID: 16333293
    [Abstract] [Full Text] [Related]

  • 26. Efficiently mining time-delayed gene expression patterns.
    Wang G, Yin L, Zhao Y, Mao K.
    IEEE Trans Syst Man Cybern B Cybern; 2010 Apr 01; 40(2):400-11. PubMed ID: 19884096
    [Abstract] [Full Text] [Related]

  • 27. Gene-Expression Omnibus integration and clustering tools in SeqExpress.
    Boyle J.
    Bioinformatics; 2005 May 15; 21(10):2550-1. PubMed ID: 15746290
    [Abstract] [Full Text] [Related]

  • 28. Clustering of gene expression data via normal mixture models.
    McLachlan GJ, Flack LK, Ng SK, Wang K.
    Methods Mol Biol; 2013 May 15; 972():103-19. PubMed ID: 23385534
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  • 32. Robust clustering using exponential power mixtures.
    Zhang J, Liang F.
    Biometrics; 2010 Dec 15; 66(4):1078-86. PubMed ID: 20163406
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  • 34. Penalized gaussian process regression and classification for high-dimensional nonlinear data.
    Yi G, Shi JQ, Choi T.
    Biometrics; 2011 Dec 15; 67(4):1285-94. PubMed ID: 21385168
    [Abstract] [Full Text] [Related]

  • 35. Analyzing gene expression time-courses.
    Schliep A, Costa IG, Steinhoff C, Schönhuth A.
    IEEE/ACM Trans Comput Biol Bioinform; 2005 Dec 15; 2(3):179-93. PubMed ID: 17044182
    [Abstract] [Full Text] [Related]

  • 36. Model-based approaches to synthesize microarray data: a unifying review using mixture of SEMs.
    Martella F, Vermunt JK.
    Stat Methods Med Res; 2013 Dec 15; 22(6):567-82. PubMed ID: 21948997
    [Abstract] [Full Text] [Related]

  • 37. Feature selection for gene expression using model-based entropy.
    Zhu S, Wang D, Yu K, Li T, Gong Y.
    IEEE/ACM Trans Comput Biol Bioinform; 2010 Dec 15; 7(1):25-36. PubMed ID: 20150666
    [Abstract] [Full Text] [Related]

  • 38. Feature selection in finite mixture of sparse normal linear models in high-dimensional feature space.
    Khalili A, Chen J, Lin S.
    Biostatistics; 2011 Jan 15; 12(1):156-72. PubMed ID: 20716532
    [Abstract] [Full Text] [Related]

  • 39. Bayesian mixture model based clustering of replicated microarray data.
    Medvedovic M, Yeung KY, Bumgarner RE.
    Bioinformatics; 2004 May 22; 20(8):1222-32. PubMed ID: 14871871
    [Abstract] [Full Text] [Related]

  • 40. Unsupervised pattern recognition: an introduction to the whys and wherefores of clustering microarray data.
    Boutros PC, Okey AB.
    Brief Bioinform; 2005 Dec 22; 6(4):331-43. PubMed ID: 16420732
    [Abstract] [Full Text] [Related]

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