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All Journal International Journal of Advanced Science Computing and Engineering
Nazirah, Nurul Ain
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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An Information Entropy Based to Identify Dominant Species for No Biological Data Genes Nazirah, Nurul Ain; Kasim, Shahreen; Meidelfi, Dwiny
International Journal of Advanced Science Computing and Engineering Vol. 2 No. 3 (2020)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1167.907 KB) | DOI: 10.62527/ijasce.2.3.101

Abstract

This report discusses about the dominant species of no biological data genes. This genes are belong to animal species. Gene is one of a process where the biological data encoded in the gene that instructed by the DNA to convert into a functional product such as protein. In gene classification, with the growth of using gene expression database, there are not enough tools to extract the gene expression from these databases. There exist over 23,000 to 50,000 genes for animal genome. So, this might contribute to data redundancy as problems can happen while handling a huge database. Therefore, to overcome the problem, many approaches to cluster and determine the dominant species have been proposed in the previous literature. For this project, in order to determine the dominant species, the information entropy based method is used. As conclusion, the purpose of this research is to identify the dominant species of no biological genes using entropy method proposed.
Co-Authors Dwiny Meidelfi Shahreen Kasim, Shahreen