NDLI: A Multiple-Filter-Multiple-Wrapper Approach to Gene Selection and Microarray Data Classification

Content Provider	ACM Digital Library
Author	Leung, Yukyee Hung, Yeungsam
Abstract	Filters and wrappers are two prevailing approaches for gene selection in microarray data analysis. Filters make use of statistical properties of each gene to represent its discriminating power between different classes. The computation is fast but the predictions are inaccurate. Wrappers make use of a chosen classifier to select genes by maximizing classification accuracy, but the computation burden is formidable. Filters and wrappers have been combined in previous studies to maximize the classification accuracy for a chosen classifier with respect to a filtered set of genes. The drawback of this single-filter-single-wrapper (SFSW) approach is that the classification accuracy is dependent on the choice of specific filter and wrapper. In this paper, a multiple-filter-multiple-wrapper (MFMW) approach is proposed that makes use of multiple filters and multiple wrappers to improve the accuracy and robustness of the classification, and to identify potential biomarker genes. Experiments based on six benchmark data sets show that the MFMW approach outperforms SFSW models (generated by all combinations of filters and wrappers used in the corresponding MFMW model) in all cases and for all six data sets. Some of MFMW-selected genes have been confirmed to be biomarkers or contribute to the development of particular cancers by other studies.
Starting Page	108
Ending Page	117
Page Count	10
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2008.46
Volume Number	7
Issue Number	1
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-01-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Filters, gene selection, hybrid classification models, microarray data classification, wrappers.
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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A Multiple-Filter-Multiple-Wrapper Approach to Gene Selection and Microarray Data Classification

Hybrid framework using multiple-filters and an embedded approach for an efficient selection and classification of microarray data

Hybrid Framework Using Multiple-Filters and an Embedded Approach for an Efficient Selection and Classification of Microarray Data

An efficient approach for microarray data classification using filter wrapper hybrid approach

Rights Creative Commons: Attribution 3.0 Hong Kong License A Multiple-Filter-Multiple-Wrapper Approach to Gene Selection and Microarray Data Classification

Title A multiple-filter-multiple-wrapper approach to gene selectionand microarray data classification

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