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Functional Hierarchical Models for Identifying Genes with Different Time-Course Expression Profiles

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  • F. Hong
  • H. Li

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  • F. Hong & H. Li, 2006. "Functional Hierarchical Models for Identifying Genes with Different Time-Course Expression Profiles," Biometrics, The International Biometric Society, vol. 62(2), pages 534-544, June.
    • Handle: RePEc:bla:biomet:v:62:y:2006:i:2:p:534-544
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2005.00505.x
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    Cited by:

    1. Coffey Norma & Hinde John, 2011. "Analyzing Time-Course Microarray Data Using Functional Data Analysis - A Review," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-32, May.
    2. Farcomeni Alessio & Arima Serena, 2012. "A Bayesian autoregressive three-state hidden Markov model for identifying switching monotonic regimes in Microarray time course data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-31, June.
    3. Shojaie Ali & Michailidis George, 2010. "Network Enrichment Analysis in Complex Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-36, May.
    4. Yu Chuan Tai & Terence P. Speed, 2009. "On Gene Ranking Using Replicated Microarray Time Course Data," Biometrics, The International Biometric Society, vol. 65(1), pages 40-51, March.

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