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Selecting informative genes of lung cancers by a combination of hybrid methods

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



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.

Item Type:Article
Additional Information:Special issue in computer science
Uncontrolled Keywords:cancer classification, genetic algorithm, gene selection, hybrid method, microarray data
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions:Geoinformation Science And Engineering (Formerly known)
ID Code:11020
Deposited By: Zalinda Shuratman
Deposited On:19 Nov 2010 02:42
Last Modified:01 Nov 2017 04:17

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