SVM-RFE With MRMR Filter for Gene Selection
Name
Mundra-2010-SVM-RFE With MRMR Filter for Gene Selection.pdf
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204.34 KB
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Author(s)
Mundra, Piyushkumar A.
Rajapakse, Jagath
Date Issued
March 2010
Journal
IEEE Transactions on NanoBioscience
Publisher
Institute of Electrical and Electronics Engineers
Citation
Mundra, P.A., and J.C. Rajapakse. “SVM-RFE With MRMR Filter for Gene Selection.” NanoBioscience, IEEE Transactions On 9.1 (2010) : 31-37. ©2010 IEEE.
Version
Final published version
Abstract
We enhance the support vector machine recursive feature elimination (SVM-RFE) method for gene selection by incorporating a minimum-redundancy maximum-relevancy (MRMR) filter. The relevancy of a set of genes are measured by the mutual information among genes and class labels, and the redundancy is given by the mutual information among the genes. The method improved identification of cancer tissues from benign tissues on several benchmark datasets, as it takes into account the redundancy among the genes during their selection. The method selected a less number of genes compared to MRMR or SVM-RFE on most datasets. Gene ontology analyses revealed that the method selected genes that are relevant for distinguishing cancerous samples and have similar functional properties. The method provides a framework for combining filter methods and wrapper methods of gene selection, as illustrated with MRMR and SVM-RFE methods.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/tnb.2009.2035284
