Ahmad, Farzana Kabir and Md Norwawi, Norita and Deris, Safaai and Othman, Nor Hayati (2008) A review of feature selection techniques via gene expression profiles. In: Proceedings - International Symposium on Information Technology 2008, ITSim. Institute of Electrical and Electronics Engineers, New York, pp. 976-982. ISBN 978-142442328-6
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Official URL: http://dx.doi.org/10.1109/ITSIM.2008.4631678
The invention of DNA microarray technology has modernized the approach of biology research in such a way that scientists can now measure the expression levels of thousands of genes simultaneously in a single experiment. Although this technology has shifted a new era in molecular classification, interpreting microarray data still remain a challenging issue due to their innate nature of "high dimensional low sample size". Therefore, robust and accurate feature selection methods are required to identify differentially expressed genes across varied samples for example between cancerous and normal cells. Successful of feature selection techniques will assist to correctly classify different cancer types and consequently led to a better understanding of genetic signatures in cancers and would improve treatment strategies. This paper presents a review of feature selection techniques that have been employed in microarray data analysis. Moreover, other problems associated with microarray data analysis also addressed. In addition, several trends were noted including highly reliance on filter techniques compared to wrapper and embedded, a growing direction towards ensemble feature selection techniques and future extension to apply feature selection in combination of heterogeneous data sources.
|Item Type:||Book Section|
|Additional Information:||International Symposium on Information Technology 2008, ITSim; Kuala Lumpur; 26 August 2008 through 29 August 2008|
|Uncontrolled Keywords:||gene expression, genes, information technology, nucleic acids, organic acids, technology differentially expressed genes, DNA microarray technologies, ensemble feature selections, expression levels, feature selection methods, feature selections, filter techniques, gene expression profiles, growing directions, heterogeneous data sources, microarray data analyses, microarray datums, molecular classifications, sample sizes, treatment strategies, feature extraction|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System|
|Deposited By:||Liza Porijo|
|Deposited On:||02 Jun 2011 09:43|
|Last Modified:||22 Jul 2011 09:08|
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