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...

Full description

Saved in:
Bibliographic Details
Main Authors: M. Othman, Razib, Deris, Safaai, Md. IIlias, Rosli
Format: Article
Language:English
Published: Elsevier Inc. 2008
Subjects:
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
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
Language: English
Description
Summary: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.