Tumor classification ranking from microarray data
نویسندگان
چکیده
منابع مشابه
Optimization Based Tumor Classification from Microarray Gene Expression Data
BACKGROUND An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally,...
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Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate...
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Feature selection is the process of choosing a subset of the original predictive variables through the elimination of redundant and uninformative representatives. An example of importance is the analysis of gene expression data from DNA microarray hybridization experiments. The data obtained from the experiments usually contain a few samples each with expression levels of a large number of gene...
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N Engl J Med 2006;354:2463-72. Copyright © 2006 Massachusetts Medical Society. D na microarray analysis was first described in the mid-1990s as a means to probe the expression of thousands of genes simultaneously1,2 and was quickly adopted by the research community for the study of a wide range of biologic processes. Most of the early studies had a simple and powerful design: to compare two bio...
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ژورنال
عنوان ژورنال: BMC Genomics
سال: 2008
ISSN: 1471-2164
DOI: 10.1186/1471-2164-9-s2-s21