Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data
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- Reilly C. & Wang C. & Rutherford M., 2003. "A Method for Normalizing Microarrays Using Genes That Are Not Differentially Expressed," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 868-878, January.
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- Allison, David B. & Gadbury, Gary L. & Heo, Moonseong & Fernandez, Jose R. & Lee, Cheol-Koo & Prolla, Tomas A. & Weindruch, Richard, 2002. "A mixture model approach for the analysis of microarray gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 1-20, March.
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Cited by:
- Hiroyuki Kasahara & Katsumi Shimotsu, 2017.
"Testing the Order of Multivariate Normal Mixture Models,"
CIRJE F-Series
CIRJE-F-1044, CIRJE, Faculty of Economics, University of Tokyo.
- Hiroyuki Kasahara & Katsumi Shimotsu, 2019. "Testing the Order of Multivariate Normal Mixture Models," Papers 1902.02920, arXiv.org.
- Douzal-Chouakria, Ahlame & Diallo, Alpha & Giroud, Françoise, 2009. "Adaptive clustering for time series: Application for identifying cell cycle expressed genes," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1414-1426, February.
- Tsai, Chieh-Yuan & Chiu, Chuang-Cheng, 2008. "Developing a feature weight self-adjustment mechanism for a K-means clustering algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4658-4672, June.
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