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A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences

A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the si...

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Main Authors: M. Othman, Razib, Deris, Safaai, Md. IIlias, Rosli
Format: Article
Language:English
Published: Elsevier Inc. 2008
Subjects:
TP Chemical technology
Online Access:http://eprints.utm.my/id/eprint/7281/1/RazibMOthman2008_AGeneticSimilarityAlgorithm.pdf
http://eprints.utm.my/id/eprint/7281/
http://dx.doi.org/10.1016/j.jbi.2007.05.010
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spelling my.utm.72812022-04-29T21:53:47Z http://eprints.utm.my/id/eprint/7281/ A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences M. Othman, Razib Deris, Safaai Md. IIlias, Rosli TP Chemical technology A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search space of the Gene Ontology graph. The genetic similarity algorithm is implemented in the Gene Ontology browser named basic UTMGO to overcome the weaknesses of the existing Gene Ontology browsers which use a conventional approach based on keyword matching. To show the applicability of the basic UTMGO, we extend its structure to develop a Gene Ontology -based protein sequence annotation tool named extended UTMGO. The objective of developing the extended UTMGO is to provide a simple and practical tool that is capable of producing better results and requires a reasonable amount of running time with low computing cost specifically for offline usage. The computational results and comparison with other related tools are presented to show the effectiveness of the proposed algorithm and tools. Elsevier Inc. 2008-02-01 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/7281/1/RazibMOthman2008_AGeneticSimilarityAlgorithm.pdf M. Othman, Razib and Deris, Safaai and Md. IIlias, Rosli (2008) A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences. Journal of Biomedical Informatics, 41 (1). pp. 65-81. ISSN 1532-0464 http://dx.doi.org/10.1016/j.jbi.2007.05.010 doi:10.1016/j.jbi.2007.05.010
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
M. Othman, Razib
Deris, Safaai
Md. IIlias, Rosli
A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
description A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search space of the Gene Ontology graph. The genetic similarity algorithm is implemented in the Gene Ontology browser named basic UTMGO to overcome the weaknesses of the existing Gene Ontology browsers which use a conventional approach based on keyword matching. To show the applicability of the basic UTMGO, we extend its structure to develop a Gene Ontology -based protein sequence annotation tool named extended UTMGO. The objective of developing the extended UTMGO is to provide a simple and practical tool that is capable of producing better results and requires a reasonable amount of running time with low computing cost specifically for offline usage. The computational results and comparison with other related tools are presented to show the effectiveness of the proposed algorithm and tools.
format Article
author M. Othman, Razib
Deris, Safaai
Md. IIlias, Rosli
author_facet M. Othman, Razib
Deris, Safaai
Md. IIlias, Rosli
author_sort M. Othman, Razib
title A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
title_short A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
title_full A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
title_fullStr A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
title_full_unstemmed A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
title_sort genetic similarity algorithm for searching the gene ontology terms and annotating anonymous protein sequences
publisher Elsevier Inc.
publishDate 2008
url http://eprints.utm.my/id/eprint/7281/1/RazibMOthman2008_AGeneticSimilarityAlgorithm.pdf
http://eprints.utm.my/id/eprint/7281/
http://dx.doi.org/10.1016/j.jbi.2007.05.010
_version_ 1732945373884841984
score 13.211869

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