The Performance Review of mRMR for Gene Selection and Classification of DNA Microarrays

Norfadzlan, Yusup and Azlan, Mohd Zain (2019) The Performance Review of mRMR for Gene Selection and Classification of DNA Microarrays. IOP Conference Series: Materials Science and Engineering, 551. pp. 1-4. ISSN 1757-899X

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Official URL: https://iopscience.iop.org/article/10.1088/1757-89...

Abstract

There are two main stages in the classification of DNA microarray data. The first stage is known as gene selection and the second stage is the classification of selected genes. The number of genes produced in high-dimensional microarrays is enormous, and only some of these genes help to identify a particular disease. The selection of relevant or informative genes that provide sufficient information about the condition is therefore essential. Gene selection is vital in reducing the data dimensionality which can ease the workload of the computer and increase the high classification performance. In this paper, we review the recent performance on one of the most popular filter based gene selection technique, maximum relevance minimum redundancy (mRMR). We also discuss several current improvements on the mRMR method.

Item Type: Article
Uncontrolled Keywords: Deoxyribonucleic Acid (DNA), DNA microarray, microarray dataset, maximum relevance minimum redundancy (mRMR).
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 25 Mar 2025 06:57
Last Modified: 25 Mar 2025 06:57
URI: http://ir.unimas.my/id/eprint/47830

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