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Analyzing Microarray Gene Expression Data
Geoffrey J. McLachlan,Kim Anh Do,Christophe Ambroise +2 more
- 04 Aug 2004
875
TL;DR: In this article, the authors proposed a supervised classification of Tissue Samples and linked the supervised classification with survival analysis, and showed that the classification of tissue samples is more accurate than that of microarray data.
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Abstract: Preface. 1. Microarrays in Gene Expression Studies. 2. Cleaning and Normalization. 3. Some Cluster Analysis Methods. 4. Clustering of Tissue Samples. 5. Screening and Clustering of Genes. 6. Discriminant Analysis. 7. Supervised Classification of Tissue Samples. 8. Linking Microarray Data with Survival Analysis. References. Author Index. Subject Index.
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A pathway-based classification method that can improve microarray-based colorectal cancer diagnosis
Hong-Qiang Wang,Xin-Ping Xie,Chun-Hou Zheng +2 more
- 11 Aug 2011
TL;DR: A pathway-based classification method that can extract pathway information through modeling gene associations in a pathway via regression and remarkably improves the performance of microarray-based colorectal cancer diagnosis is developed.
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