Conceptual Clustering of RNA Sequences with Codon Usage Model

Dr. Barilee Baridam; Dr. Olumide Owolabi

Conceptual Clustering of RNA Sequences with Codon Usage Model

Dr. Barilee Baridam * §

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Dr. Olumide Owolabi

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University of Pretoria

Conceptual Clustering of RNA Sequences with Codon Usage Model

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Abstract

This paper proposes a conceptual clustering approachfor RNA sequences using codons. It is shown thatemploying the codons (codon usage model) in the conceptualclustering of RNA sequences has high efficiency and robustnesscompared to conventional clustering methods. In cases wherethere are hidden structural patterns, homology search algorithmsare inefficient in locating similar sequences and as a result arenot reliable in the task of biological sequence clustering. As isshown by empirical results in this paper, conceptual clusteringusing the codons is able to discover similar sequences in adatabase of sequences with hidden structural homologues. Thecodon usage and cohesiveness model introduced in this papercan be efficiently employed in clustering biological sequence datawhere conventional homology search algorithms fail.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Baridam, Dr. Owolabi, Dr. Baridam. 1970. "Conceptual Clustering of RNA Sequences with Codon Usage Model". Global Journal of Computer Science and Technology GJCST Volume 10 (GJCST Volume 10 Issue 8).

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GJCST Volume 10 Issue 8

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Submission ReceivedFebruary 10, 2010
Peer Review Double Blind
Handling Editor
Accepted March 2, 2010
Published March 15, 2010

Version of record

v1.2

Issue date

September 20, 2010

Language

English

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Article Matrices

Total Score: 152

Country: Unknown

Subject: Global Journal of Computer Science and Technology

Authors: Dr. Barilee Baridam, Dr. Olumide Owolabi (PhD/Dr. count: 2)

View Count (all-time): 138

Total Views (Real + Logic): 5554

Total Downloads (simulated): 266

Publish Date: 2010 03, Mon

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Total Views: 5.6K

Total Downloads: 266

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