Integrative gene selection for classification of microarray data
Microarray data classification is one of the major interests in health informatics that aims at discovering hidden patterns in gene expression profiles. The main challenge in building this classification system is the curse of dimensionality problem. Thus, there is a considerable amount of studies o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Canadian Center of Science and Education
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/22460/1/22460.pdf |
| _version_ | 1796970165209923584 |
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| author | Ong, Huey Fang Mustapha, Norwati Sulaiman, Md. Nasir |
| author_facet | Ong, Huey Fang Mustapha, Norwati Sulaiman, Md. Nasir |
| author_sort | Ong, Huey Fang |
| collection | UPM |
| description | Microarray data classification is one of the major interests in health informatics that aims at discovering hidden patterns in gene expression profiles. The main challenge in building this classification system is the curse of dimensionality problem. Thus, there is a considerable amount of studies on gene selection method for building effective classification models. However, most of the approaches consider solely on gene expression values, and as a result, the selected genes might not be biologically meaningful. This paper presents an integrative gene selection for improving microarray data classification performance. The proposed approach employs the association analysis technique to integrate both gene expression and biological data in identifying informative genes. The experimental results show that the proposed gene selection outperformed the traditional method in terms of accuracy and number of selected genes. |
| first_indexed | 2024-03-06T07:54:00Z |
| format | Article |
| id | upm.eprints-22460 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T07:54:00Z |
| publishDate | 2011 |
| publisher | Canadian Center of Science and Education |
| record_format | dspace |
| spelling | upm.eprints-224602016-06-08T08:57:22Z http://psasir.upm.edu.my/id/eprint/22460/ Integrative gene selection for classification of microarray data Ong, Huey Fang Mustapha, Norwati Sulaiman, Md. Nasir Microarray data classification is one of the major interests in health informatics that aims at discovering hidden patterns in gene expression profiles. The main challenge in building this classification system is the curse of dimensionality problem. Thus, there is a considerable amount of studies on gene selection method for building effective classification models. However, most of the approaches consider solely on gene expression values, and as a result, the selected genes might not be biologically meaningful. This paper presents an integrative gene selection for improving microarray data classification performance. The proposed approach employs the association analysis technique to integrate both gene expression and biological data in identifying informative genes. The experimental results show that the proposed gene selection outperformed the traditional method in terms of accuracy and number of selected genes. Canadian Center of Science and Education 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/22460/1/22460.pdf Ong, Huey Fang and Mustapha, Norwati and Sulaiman, Md. Nasir (2011) Integrative gene selection for classification of microarray data. Computer and Information Science, 4 (2). pp. 55-63. ISSN 1913-8989; ESSN: 1913-8997 http://www.ccsenet.org/journal/index.php/cis/article/view/8687 10.5539/cis.v4n2p55 |
| spellingShingle | Ong, Huey Fang Mustapha, Norwati Sulaiman, Md. Nasir Integrative gene selection for classification of microarray data |
| title | Integrative gene selection for classification of microarray data |
| title_full | Integrative gene selection for classification of microarray data |
| title_fullStr | Integrative gene selection for classification of microarray data |
| title_full_unstemmed | Integrative gene selection for classification of microarray data |
| title_short | Integrative gene selection for classification of microarray data |
| title_sort | integrative gene selection for classification of microarray data |
| url | http://psasir.upm.edu.my/id/eprint/22460/1/22460.pdf |
| work_keys_str_mv | AT onghueyfang integrativegeneselectionforclassificationofmicroarraydata AT mustaphanorwati integrativegeneselectionforclassificationofmicroarraydata AT sulaimanmdnasir integrativegeneselectionforclassificationofmicroarraydata |