Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine
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- Park, Changyi & Koo, Ja-Yong & Kim, Sujong & Sohn, Insuk & Lee, Jae Won, 2008. "Classification of gene functions using support vector machine for time-course gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2578-2587, January.
- Dudoit S. & Fridlyand J. & Speed T. P, 2002. "Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 77-87, March.
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- Drechsler, Jörg & Reiter, Jerome P., 2011. "An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3232-3243, December.
- Insuk Sohn & Jooyong Shim & Changha Hwang & Sujong Kim & Jae Won Lee, 2014. "Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 573-581, March.
- Wenyan Zhong & Jingjing Wu, 2017. "Feature Selection for Cancer Classification Using Microarray Gene Expression Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 1(2), pages 33-39, April.
- Ramos, Sandra & Amaral Turkman, Antónia & Antunes, Marília, 2010. "Bayesian classification for bivariate normal gene expression," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 2012-2020, August.
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