Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study

Expressed Sequence Tag (EST) plays an important role in discovering the full length of a gene. Therefore clustering of ESTs remains an interesting area for further exploration. We investigate several available clustering algorithms, and then we propose and evaluate an unsuperivsed clustering method...

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Main Authors: Ng, Keng Hoong, Somnuk, Phon Amnuaisuk, Ho, Chin Kuan
Format: Conference or Workshop Item
Published: 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2836/
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author Ng, Keng Hoong
Somnuk, Phon Amnuaisuk
Ho, Chin Kuan
author_facet Ng, Keng Hoong
Somnuk, Phon Amnuaisuk
Ho, Chin Kuan
author_sort Ng, Keng Hoong
building MMU Institutional Repository
collection Online Access
description Expressed Sequence Tag (EST) plays an important role in discovering the full length of a gene. Therefore clustering of ESTs remains an interesting area for further exploration. We investigate several available clustering algorithms, and then we propose and evaluate an unsuperivsed clustering method that uses Markov models and Se self-organizing maps. The initial evaluation of the method gives satisfactory result, where its clustering accuracy is up to 80.08%.
first_indexed 2025-11-14T18:08:14Z
format Conference or Workshop Item
id mmu-2836
institution Multimedia University
institution_category Local University
last_indexed 2025-11-14T18:08:14Z
publishDate 2008
recordtype eprints
repository_type Digital Repository
spelling mmu-28362023-04-12T08:18:25Z http://shdl.mmu.edu.my/2836/ Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study Ng, Keng Hoong Somnuk, Phon Amnuaisuk Ho, Chin Kuan T Technology (General) QA75.5-76.95 Electronic computers. Computer science Expressed Sequence Tag (EST) plays an important role in discovering the full length of a gene. Therefore clustering of ESTs remains an interesting area for further exploration. We investigate several available clustering algorithms, and then we propose and evaluate an unsuperivsed clustering method that uses Markov models and Se self-organizing maps. The initial evaluation of the method gives satisfactory result, where its clustering accuracy is up to 80.08%. 2008-08 Conference or Workshop Item NonPeerReviewed Ng, Keng Hoong and Somnuk, Phon Amnuaisuk and Ho, Chin Kuan (2008) Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study. In: International Symposium on Information Technology , 26-29 AUG 2008 , Univ Kebangsaan, Fac Informat Sci & Technol, Kuala Lumpur, MALAYSIA. http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=1&SID=V1OJnefKFf4@FFPHd@m&page=87&doc=870
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
Ng, Keng Hoong
Somnuk, Phon Amnuaisuk
Ho, Chin Kuan
Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study
title Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study
title_full Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study
title_fullStr Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study
title_full_unstemmed Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study
title_short Clustering of Expressed Sequence Tag (EST) with Markov Models and Self-Organizing Maps: An Exploratory Study
title_sort clustering of expressed sequence tag (est) with markov models and self-organizing maps: an exploratory study
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2836/
http://shdl.mmu.edu.my/2836/