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Gene selection via the BAHSIC family of algorithms

Song, Le; Bedo, Justin; Borgwardt, Karsten; Gretton, Arthur; Smola, Alexander

Description

Motivation: Identifying significant genes among thousands of sequences on a microarray is a central challenge for cancer research in bioinformatics. The ultimate goal is to detect the genes that are involved in disease outbreak and progression. A multitude of methods have been proposed for this task of feature selection, yet the selected gene lists differ greatly between different methods. To accomplish biologically meaningful gene selection from microarray data, we have to understand the...[Show more]

CollectionsANU Research Publications
Date published: 2007
Type: Journal article
URI: http://hdl.handle.net/1885/51592
Source: Bioinformatics
DOI: 10.1093/bioinformatics/btm216

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