Knowledge-based analysis of microarray gene expression data by using support vector machines
Description:
The authors introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering…
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Date:
June 18, 2001
Creator:
Grundy, William; Manuel Ares, Jr. & Haussler, David
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