SVM-RFE With MRMR Filter for Gene Selection
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 gi...
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2011
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| Online Access: | http://hdl.handle.net/1721.1/62171 |
| _version_ | 1826190164186103808 |
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| author | Mundra, Piyushkumar A. Rajapakse, Jagath |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Mundra, Piyushkumar A. Rajapakse, Jagath |
| author_sort | Mundra, Piyushkumar A. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T08:36:04Z |
| format | Article |
| id | mit-1721.1/62171 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:36:04Z |
| publishDate | 2011 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/621712022-09-30T09:53:05Z SVM-RFE With MRMR Filter for Gene Selection Mundra, Piyushkumar A. Rajapakse, Jagath Massachusetts Institute of Technology. Department of Biological Engineering Rajapakse, Jagath Rajapakse, Jagath 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. 2011-04-08T15:12:53Z 2011-04-08T15:12:53Z 2010-03 2009-10 Article http://purl.org/eprint/type/JournalArticle 1536-1241 INSPEC Accession Number: 11206252 http://hdl.handle.net/1721.1/62171 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. 19884101 en_US http://dx.doi.org/10.1109/tnb.2009.2035284 IEEE Transactions on NanoBioscience 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. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Mundra, Piyushkumar A. Rajapakse, Jagath SVM-RFE With MRMR Filter for Gene Selection |
| title | SVM-RFE With MRMR Filter for Gene Selection |
| title_full | SVM-RFE With MRMR Filter for Gene Selection |
| title_fullStr | SVM-RFE With MRMR Filter for Gene Selection |
| title_full_unstemmed | SVM-RFE With MRMR Filter for Gene Selection |
| title_short | SVM-RFE With MRMR Filter for Gene Selection |
| title_sort | svm rfe with mrmr filter for gene selection |
| url | http://hdl.handle.net/1721.1/62171 |
| work_keys_str_mv | AT mundrapiyushkumara svmrfewithmrmrfilterforgeneselection AT rajapaksejagath svmrfewithmrmrfilterforgeneselection |