Feature selection methods for big data bioinformatics: A survey from the search perspective

This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search p...

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Bibliographic Details
Published in:	Methods (San Diego, Calif.) Vol. 111; pp. 21 - 31
Main Authors:	Wang, Lipo, Wang, Yaoli, Chang, Qing
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.12.2016
Subjects:	Algorithms Artificial Intelligence bioinformatics Biomarkers Classification Clustering Computational biology Computational Biology - methods Computational Biology - trends Computational intelligence data collection Data mining Data Mining - methods Data Mining - trends Evolutionary algorithms Evolutionary computation Fuzzy logic Genetic algorithms Humans Machine learning Microarray Neural networks Particle swarm optimization Pattern recognition Random forests Rough sets Soft computing Software Support vector machines surveys Swarm intelligence systematic review Evolutionary computation Evolutionary algorithms Pattern recognition Soft computing Clustering Data mining Microarray Particle swarm optimization Random forests Genetic algorithms Fuzzy logic Support vector machines Neural networks Rough sets Classification Machine learning Biomarkers Swarm intelligence Computational intelligence Computational biology
ISSN:	1046-2023, 1095-9130
Online Access:	Get full text
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