Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin

Gene expression analysis is one of the studies in bioinformatics. There are many methods and approaches use in gene expression analysis. Some methods that are currently being used, such as fuzzy ART, neural network, and Bayesian method were used in gene expression analysis. The problem that occur...

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Main Author:	Zainal Ahbiddin, Mohd Dzulkarnain
Format:	Thesis
Language:	English
Published:	2006
Subjects:	Electronic Computers Computer Science
Online Access:	https://ir.uitm.edu.my/id/eprint/1602/1/TD_MOHD%20DZULKARNAIN%20ZAINAL%20AHBIDDIN%20CS%2007_5%20P01.pdf
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id	my-uitm-ir.1602
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spelling	my-uitm-ir.16022019-07-19T07:46:25Z Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin 2006 Zainal Ahbiddin, Mohd Dzulkarnain Electronic Computers. Computer Science Gene expression analysis is one of the studies in bioinformatics. There are many methods and approaches use in gene expression analysis. Some methods that are currently being used, such as fuzzy ART, neural network, and Bayesian method were used in gene expression analysis. The problem that occurred in supervised learning is that the output and error rates that been provided were momentous. The reason in conducting this research is to determine the best methods, between two approaches for gene expression analysis. For this research, the approach used is supervised learning and the methods that were used are multi layer feedforward and k-Nearest Neighbour. The methodology that will be use for this research are knowledge acquisition, implementation that consists of three phase; experiment, result and analysis, experiments and observation, and evaluation and findings. After a series of experiments, the multi layer feedforward is the better method in determining gene expression especially protein genes rather than k-Nearest Neighbour. It is because the accuracy of the output is more precise and can be used for further analysis. The presentation of multilayer feedforward is clear and well-defined. The accuracy of the results is important for usage of others. This research can be a good reference for the advancement and development of gene expression analysis. 2006 Thesis https://ir.uitm.edu.my/id/eprint/1602/ https://ir.uitm.edu.my/id/eprint/1602/1/TD_MOHD%20DZULKARNAIN%20ZAINAL%20AHBIDDIN%20CS%2007_5%20P01.pdf text en public degree Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Electronic Computers Computer Science
spellingShingle	Electronic Computers Computer Science Zainal Ahbiddin, Mohd Dzulkarnain Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin
description	Gene expression analysis is one of the studies in bioinformatics. There are many methods and approaches use in gene expression analysis. Some methods that are currently being used, such as fuzzy ART, neural network, and Bayesian method were used in gene expression analysis. The problem that occurred in supervised learning is that the output and error rates that been provided were momentous. The reason in conducting this research is to determine the best methods, between two approaches for gene expression analysis. For this research, the approach used is supervised learning and the methods that were used are multi layer feedforward and k-Nearest Neighbour. The methodology that will be use for this research are knowledge acquisition, implementation that consists of three phase; experiment, result and analysis, experiments and observation, and evaluation and findings. After a series of experiments, the multi layer feedforward is the better method in determining gene expression especially protein genes rather than k-Nearest Neighbour. It is because the accuracy of the output is more precise and can be used for further analysis. The presentation of multilayer feedforward is clear and well-defined. The accuracy of the results is important for usage of others. This research can be a good reference for the advancement and development of gene expression analysis.
format	Thesis
qualification_level	Bachelor degree
author	Zainal Ahbiddin, Mohd Dzulkarnain
author_facet	Zainal Ahbiddin, Mohd Dzulkarnain
author_sort	Zainal Ahbiddin, Mohd Dzulkarnain
title	Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin
title_short	Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin
title_full	Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin
title_fullStr	Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin
title_full_unstemmed	Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin
title_sort	comparative revision of artificial intelligent methods for discovering gene expression / mohd dzulkarnain zainal ahbiddin
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2006
url	https://ir.uitm.edu.my/id/eprint/1602/1/TD_MOHD%20DZULKARNAIN%20ZAINAL%20AHBIDDIN%20CS%2007_5%20P01.pdf
_version_	1783733036589776896

Comparative revision of artificial intelligent methods for discovering gene expression / Mohd Dzulkarnain Zainal Ahbiddin

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