title: A review of feature selection techniques in bioinformatics.
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.
authors.affiliation: Department of Plant Systems Biology, VIB, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be
authors.forename: Yvan
authors.initials: Y
authors.lastname: Saeys
authors.forename: Iñaki
authors.initials: I
authors.lastname: Inza
authors.forename: Pedro
authors.initials: P
authors.lastname: Larrañaga
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D017421:Sequence Analysis / Q000379:methods*