Scinovex
reviewTop 1% cited

A review of feature selection techniques in bioinformatics

Bioinformatics · 2007 · Vol. 23(19) · pp. 2507–2517
Yvan SaeysIñaki InzaPedro Larrañaga

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.

Gene expression and cancer classificationMachine Learning in BioinformaticsBioinformatics and Genomic NetworksFeature selectionComputer scienceVariety (cybernetics)Selection (genetic algorithm)Feature (linguistics)Machine learningData scienceArtificial intelligenceData miningBioinformatics

MeSH terms

AlgorithmsArtificial IntelligenceComputer SimulationModels, BiologicalPattern Recognition, AutomatedSequence AnalysisComputational BiologyGene Expression Profiling

Funding

  • Eusko Jaurlaritza
  • Universiteit Gent
Citations
5,229
FWCI
42.49
field-weighted impact
References
163
Percentile
100%
vs. same field & year
Citations per year
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.