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A Review of Cancer Classification Software for Gene Expression Data

Tan, Ching Siang and Ting, Wai Soon and Shahreen, Kasim and Mohd Saberi, Mohamad and Chan, Weng Howe and Safaai, Deris and Zalmiyah, Zakaria and Zuraini, Ali Shah and Zuwairie, Ibrahim (2015) A Review of Cancer Classification Software for Gene Expression Data. International Journal of Bio-Science and Bio-Technology (IJBSBT), 7 (4). pp. 89-108. ISSN 2233-7849

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Abstract

Microarray technology provides a way for researchers to measure the expression level of thousands of genes simultaneously in a single experiment. Due to the increasing amount of microarray data, the field of microarray data analysis has become a major topic among researchers. One of the examples of microarray data analysis is classification. Classification is the process of determining the classes for samples. The goal of classification is to identify the differentially expressed genes so that these genes can be used to predict the classes for new samples. In order to perform the tasks of classification of microarray data, classification software is required for effective classification and analysis of large-scale data. This paper reviews numerous classification software applications for gene expression data. In this paper, the reviewed software can be categorized into six supervised classification methods: Support Vector Machine, K-Nearest Neighbour, Neural Network, Linear Discriminant Analysis, Bayesian Classifier, and Random Forest.

Item Type: Article
Uncontrolled Keywords: Cancer Classification, Gene Expression Data, Microarray, Supervised Classification Methods, Bioinformatics, Artificial Intelligence
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 21 Dec 2015 02:31
Last Modified: 08 Feb 2018 02:58
URI: http://umpir.ump.edu.my/id/eprint/11602
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