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Gene Selection for Cancer Classification using Support Vector Machines

by: Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik
Machine Learning, Vol. 46, No. 1. (1 January 2002), pp. 389-422, doi:10.1023/a:1012487302797  Key: citeulike:1138538

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Abstract

DNA micro-arrays now permit scientists to screen thousands of genes simultaneously and determine whether those genes are active, hyperactive or silent in normal or cancerous tissue. Because these new micro-array devices generate bewildering amounts of raw data, new analytical methods must be developed to sort out whether cancer tissues have distinctive signatures of gene expression over normal tissues or other types of cancer tissues.


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