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  Improved gene selection for classification of microarrays

Jäger, J., Sengupta, R., & Ruzzo, W. L. (2003). Improved gene selection for classification of microarrays. /: /.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-8B41-3 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-8B42-1
Genre: Proceedings

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Jaeger.pdf (Any fulltext), 251KB
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 Creators:
Jäger, J.1, Author
Sengupta, R., Author
Ruzzo, W. L., Author
Affiliations:
1Max Planck Society, ou_persistent13              

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 Abstract: In this paper we derive a method for evaluating and improving techniques for selecting informative genes from microarray data. Genes of interest are typically selected by ranking genes according to a test-statistic and then choosing the top k genes. A problem with this approach is that many of these genes are highly correlated. For classification purposes it would be ideal to have distinct but still highly informative genes. We propose three different pre-filter methods — two based on clustering and one based on correlation — to retrieve groups of similar genes. For these groups we apply a test-statistic to finally select genes of interest. We show that this filtered set of genes can be used to significantly improve existing classifiers.

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Language(s): eng - English
 Dates: 2003
 Publication Status: Published in print
 Pages: /
 Publishing info: / : /
 Table of Contents: -
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 Identifiers: eDoc: 191977
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Title: 8th Pacific Symposium on Biocomputing (PSB 2003)
Place of Event: Lihue, Hawaii, USA
Start-/End Date: 2003-01-03 - 2003-01-07

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