Shi, T. W. and Kah, W. S. and Mohamad, M. S. and Moorthy, K. and Deris, S. and Sjaugi, M. F. and Omatu, S. and Corchado, J. M. and Kasim, S. (2017) A review of gene selection tools in classifying cancer microarray data. Current Bioinformatics, 12 (3). pp. 202-212. ISSN 1574-8936
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Official URL: http://dx.doi.org/10.2174/157489361066615102621510...
Abstract
Background: The measurement of expression levels of many genes through a single experiment is now possible due to the development of DNA microarray technology. However, many computational methods are having difficulties in selecting a small subset of genes because there are a few samples compared to the huge number of genes, irrelevant genes and noisy genes. Objective: This paper presents a review of existing tools for gene selection divided into four different categories. Method: In addition, most studies focus on selecting a small subset without analysing the genes’ functional and biological characteristics. Many researchers are continuously seeking solutions to this problem. Microarray data analysis has been successfully applied to gene selection algorithms in a different development environment. Results: Many different tools have been generated for gene selection in classifying microarray data. Conclusion: A suitable and user-friendly tool for users and biomedical researchers should be developed to avoid selection biases and allow analysis of multiple solutions.
Item Type: | Article |
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Uncontrolled Keywords: | cancer classification, gene selection, MATLAB |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computing |
ID Code: | 80882 |
Deposited By: | Narimah Nawil |
Deposited On: | 24 Jul 2019 00:08 |
Last Modified: | 24 Jul 2019 00:08 |
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