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A Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification

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  • Ming Yuan
  • Christina Kendziorski

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  • Ming Yuan & Christina Kendziorski, 2006. "A Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification," Biometrics, The International Biometric Society, vol. 62(4), pages 1089-1098, December.
  • Handle: RePEc:bla:biomet:v:62:y:2006:i:4:p:1089-1098
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00611.x
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    References listed on IDEAS

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    1. George C. Tseng & Wing H. Wong, 2005. "Tight Clustering: A Resampling-Based Approach for Identifying Stable and Tight Patterns in Data," Biometrics, The International Biometric Society, vol. 61(1), pages 10-16, March.
    2. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
    3. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
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    Cited by:

    1. Marín Díazaraque, Juan Miguel & Rodríguez Bernal, M. T., 2010. "Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis," DES - Working Papers. Statistics and Econometrics. WS ws104427, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Elisa C. J. Maria & Isabel Salazar & Luis Sanz & Miguel A. Gómez-Villegas, 2020. "Using Copula to Model Dependence When Testing Multiple Hypotheses in DNA Microarray Experiments: A Bayesian Approximation," Mathematics, MDPI, vol. 8(9), pages 1-22, September.
    3. Marín, J.M. & Rodríguez-Bernal, M.T., 2012. "Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1898-1907.

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