A review of feature selection techniques in bioinformatics
Yvan Saeys1 Department 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, SpainIñaki Inza1 Department 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, SpainPedro Larrañaga1 Department 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
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Abstract
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: [email protected] Supplementary information: http://bioinformatics.psb.ugent.be/supplementary_data/yvsae/fsreview
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