A review of feature selection and feature extraction methods applied on microarray data.
Author(s)
Hira, ZM
Gillies, DF
Type
Journal Article
Abstract
© 2015 Zena M. Hira and Duncan F. Gillies.We summarise various ways of performing dimensionality reduction on high-dimensional microarray data. Many different feature selection and feature extraction methods exist and they are being widely used. All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. A popular source of data is microarrays, a biological platform for gathering gene expressions. Analysing microarrays can be difficult due to the size of the data they provide. In addition the complicated relations among the different genes make analysis more difficult and removing excess features can improve the quality of the results. We present some of the most popular methods for selecting significant features and provide a comparison between them. Their advantages and disadvantages are outlined in order to provide a clearer idea of when to use each one of them for saving computational time and resources.
Date Issued
2015-01-01
ISSN
1687-8027
Start Page
198363
Journal / Book Title
Adv Bioinformatics
Volume
2015
Copyright Statement
© 2015 Z. M. Hira and D. F. Gillies. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited. (http://creativecommons.org/licenses/by/3.0/)
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited. (http://creativecommons.org/licenses/by/3.0/)
License URL
Description
20.07.15 KB. Ok to add published version to spiral, OA paper
Identifier
http://www.ncbi.nlm.nih.gov/pubmed/26170834
Coverage Spatial
Egypt