A Cancer Gene Selection Algorithm Based on the K-S Test and CFS
Joint Authors
Chen, Fuxue
Su, Qiang
Wang, Yina
Jiang, Xiaobing
Lu, W. C.
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-08
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Background.
To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S) test and correlation-based feature selection (CFS) principles.
The algorithm selects distinguished genes first using the K-S test, and then, it uses CFS to select genes from those selected by the K-S test.
Results.
We adopted support vector machines (SVM) as the classification tool and used the criteria of accuracy to evaluate the performance of the classifiers on the selected gene subsets.
This approach compared the proposed gene subset selection algorithm with the K-S test, CFS, minimum-redundancy maximum-relevancy (mRMR), and ReliefF algorithms.
The average experimental results of the aforementioned gene selection algorithms for 5 gene expression datasets demonstrate that, based on accuracy, the performance of the new K-S and CFS-based algorithm is better than those of the K-S test, CFS, mRMR, and ReliefF algorithms.
Conclusions.
The experimental results show that the K-S test-CFS gene selection algorithm is a very effective and promising approach compared to the K-S test, CFS, mRMR, and ReliefF algorithms.
American Psychological Association (APA)
Su, Qiang& Wang, Yina& Jiang, Xiaobing& Chen, Fuxue& Lu, W. C.. 2017. A Cancer Gene Selection Algorithm Based on the K-S Test and CFS. BioMed Research International،Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1134089
Modern Language Association (MLA)
Su, Qiang…[et al.]. A Cancer Gene Selection Algorithm Based on the K-S Test and CFS. BioMed Research International No. 2017 (2017), pp.1-6.
https://search.emarefa.net/detail/BIM-1134089
American Medical Association (AMA)
Su, Qiang& Wang, Yina& Jiang, Xiaobing& Chen, Fuxue& Lu, W. C.. A Cancer Gene Selection Algorithm Based on the K-S Test and CFS. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1134089
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1134089