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Bioinformatics Advance Access originally published online on August 24, 2007
Bioinformatics 2007 23(19):2507-2517; doi:10.1093/bioinformatics/btm344
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A review of feature selection techniques in bioinformatics

Yvan Saeys 1,*, Iñaki Inza 2 and Pedro Larrañaga 2

1Department of Plant Systems Biology, VIB, B-9052 Ghent, Belgium and Bioinformatics and Evolutionary Genomics group, Department of Molecular Genetics, Ghent University, B-9052 Ghent, Belgium and 2Department of Computer Science and Artificial Intelligence, Computer Science Faculty, University of the Basque Country, Paseo Manuel de Lardizabal 1, 20018 Donostia - San Sebastián, Spain

*To whom correspondence should be addressed.


  Abstract

Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques.

In this article, we make the interested reader aware of the possibilities of feature selection, providing a basic taxonomy of feature selection techniques, and discussing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications.

Contact: yvan.saeys{at}psb.ugent.be

Supplementary information: http://bioinformatics.psb.ugent.be/supplementary_data/yvsae/fsreview

Associate Editor: Jonathan Wren

Received on April 17, 2007; revised on June 11, 2007; accepted on June 25, 2007

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