reviewTop 1% cited
A review of feature selection techniques in bioinformatics
Bioinformatics · 2007 · Vol. 23(19) · pp. 2507–2517
Yvan Saeys✉(University of the Basque Country)Iñaki Inza(Ghent University)Pedro Larrañaga(Ghent University)
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
Cited by
A hybrid particle swarm optimization for feature subset selection by integrating a novel local search strategy
Applied Soft Computing · 2016 · 373 citations
Feature selection and analysis on correlated gas sensor data with recursive feature elimination
Sensors and Actuators B Chemical · 2015 · 516 citations
A review of microarray datasets and applied feature selection methods
Information Sciences · 2014 · 666 citations
Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification
Applied Soft Computing · 2017 · 421 citations
Learning from class-imbalanced data: Review of methods and applications
Expert Systems with Applications · 2016 · 2,276 citations
Inferring Pathway Activity toward Precise Disease Classification
PLoS Computational Biology · 2008 · 615 citations
Feature Selection
ACM Computing Surveys · 2017 · 2,235 citations
Inferring Regulatory Networks from Expression Data Using Tree-Based Methods
PLoS ONE · 2010 · 2,212 citations
References
Gene selection and classification of microarray data using random forest
BMC Bioinformatics · 2006 · 2,930 citations
Systematic variation in gene expression patterns in human cancer cell lines
Nature Genetics · 2000 · 2,090 citations
Selecting a Maximally Informative Set of Single-Nucleotide Polymorphisms for Association Analyses Using Linkage Disequilibrium
The American Journal of Human Genetics · 2004 · 1,602 citations
Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments
FEBS Letters · 2004 · 1,517 citations
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
Proceedings of the National Academy of Sciences · 1999 · 4,201 citations
A Direct Approach to False Discovery Rates
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2002 · 5,723 citations
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring
Science · 1999 · 11,587 citations
Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling
Cancer Cell · 2002 · 1,917 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.
