A Review of Gene Selection Tools in Classifying Cancer Microarray Data
| Autor: | Mohd Saberi Mohamad, Wong S. Kah, Sigeru Omatu, Muhammad Farhan Sjaugi, Kohbalan Moorthy, Juan M. Corchado, Shahreen Kasim, Tham Wen Shi, Safaai Deris |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Development environment User Friendly Computer science Microarray analysis techniques Computational biology computer.software_genre Biochemistry Expression (mathematics) 03 medical and health sciences Computational Mathematics 030104 developmental biology Gene selection Genetics Data mining DNA microarray Molecular Biology Gene computer Selection (genetic algorithm) |
| Zdroj: | Current Bioinformatics. 12:202-212 |
| ISSN: | 1574-8936 |
| DOI: | 10.2174/1574893610666151026215104 |
| Popis: | 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. However, many 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. Many different tools have been generated for gene selection in classifying microarray data. A suitable and user friendly tool for users and biomedical researchers should be developed to avoid selection biases and allow analysis of multiple solutions. This paper presents a review of existing tools for gene selection divided into four different categories. |
| Databáze: | OpenAIRE |
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