Universiti Teknologi Malaysia Institutional Repository

An approach using hybrid methods to select informative genes from microarray data for cancer classification

Mohamad, Mohd. Sabri and Omatu, Sigeru and Yoshioka, Michifumi and Deris, Safaai (2008) An approach using hybrid methods to select informative genes from microarray data for cancer classification. In: Second Asia International Conference on Modelling & Simulation.

[img] PDF
Restricted to Repository staff only


Official URL: http://dx.doi.org/10.1109/AMS.2008.71


Recent advances in microarray technology allow scientists to measure expression levels of thousands of genes simultaneously in human tissue samples. This technology has been increasingly used in cancer research because of its potential for classification of the tissue samples based only on gene expression levels. A major problem in these microarray data is that the number of genes greatly exceeds the number of tissue samples. Moreover, these data have a noisy nature. It has been shown from literature review 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 is most relevant for the cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed on two well-known microarray data. The experimental results have shown that the gene subsets are very small in size and yield better classification accuracy as compared with other previous works as well as four methods experimented in this work. In addition, a list of informative genes in the best subsets is also presented for biological usage

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Gene selection, hybrid method, cancer classification, microarray data, gene expression
Subjects:T Technology > T Technology (General)
Divisions:Computer Science and Information System (Formerly known)
ID Code:7398
Deposited By: Nur Amal Zakiah Shamsudin
Deposited On:02 Jan 2009 07:22
Last Modified:01 Jun 2010 15:51

Repository Staff Only: item control page