Selecting informative genes of lung cancers by a combination of hybrid methods
Gene expression technology namely microarray, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of efficient cancer diagnosis and classification platform. A major...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Penerbit UTM Press
2008
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| Online Access: | http://eprints.utm.my/11020/ http://eprints.utm.my/11020/1/MohdSaberiMohamad2008_SelectingInformativeGenesOfLung.pdf |
| _version_ | 1848892237462634496 |
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| author | Mohamad, Mohd. Saberi Omatu, Sigeru Deris, Safaai Yoshioka, Michifuci |
| author_facet | Mohamad, Mohd. Saberi Omatu, Sigeru Deris, Safaai Yoshioka, Michifuci |
| author_sort | Mohamad, Mohd. Saberi |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Gene expression technology namely microarray, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data have also noisy genes. It has been shown from literature reviews that selecting a small subset of informative genes can lead to an improved classification accuracy. Thus, this paper aims to select a small subset of informative genes that are most relevant for the cancer classification. To achieve this aim, an approach that involved two hybrid methods has been proposed. This approach is assessed and evaluated on one well-known microarray data set, namely the lung cancer, showing competitive results. |
| first_indexed | 2025-11-15T21:10:40Z |
| format | Article |
| id | utm-11020 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T21:10:40Z |
| publishDate | 2008 |
| publisher | Penerbit UTM Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-110202017-11-01T04:17:22Z http://eprints.utm.my/11020/ Selecting informative genes of lung cancers by a combination of hybrid methods Mohamad, Mohd. Saberi Omatu, Sigeru Deris, Safaai Yoshioka, Michifuci QA75 Electronic computers. Computer science RC0254 Neoplasms. Tumors. Oncology (including Cancer) Gene expression technology namely microarray, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data have also noisy genes. It has been shown from literature reviews that selecting a small subset of informative genes can lead to an improved classification accuracy. Thus, this paper aims to select a small subset of informative genes that are most relevant for the cancer classification. To achieve this aim, an approach that involved two hybrid methods has been proposed. This approach is assessed and evaluated on one well-known microarray data set, namely the lung cancer, showing competitive results. Penerbit UTM Press 2008-12 Article PeerReviewed application/pdf en http://eprints.utm.my/11020/1/MohdSaberiMohamad2008_SelectingInformativeGenesOfLung.pdf Mohamad, Mohd. Saberi and Omatu, Sigeru and Deris, Safaai and Yoshioka, Michifuci (2008) Selecting informative genes of lung cancers by a combination of hybrid methods. Jurnal Teknologi Maklumat, 20 (3). pp. 149-157. ISSN 0128-3790 |
| spellingShingle | QA75 Electronic computers. Computer science RC0254 Neoplasms. Tumors. Oncology (including Cancer) Mohamad, Mohd. Saberi Omatu, Sigeru Deris, Safaai Yoshioka, Michifuci Selecting informative genes of lung cancers by a combination of hybrid methods |
| title | Selecting informative genes of lung cancers by a combination of hybrid methods |
| title_full | Selecting informative genes of lung cancers by a combination of hybrid methods |
| title_fullStr | Selecting informative genes of lung cancers by a combination of hybrid methods |
| title_full_unstemmed | Selecting informative genes of lung cancers by a combination of hybrid methods |
| title_short | Selecting informative genes of lung cancers by a combination of hybrid methods |
| title_sort | selecting informative genes of lung cancers by a combination of hybrid methods |
| topic | QA75 Electronic computers. Computer science RC0254 Neoplasms. Tumors. Oncology (including Cancer) |
| url | http://eprints.utm.my/11020/ http://eprints.utm.my/11020/1/MohdSaberiMohamad2008_SelectingInformativeGenesOfLung.pdf |