DNA MOTIF IDENTIFICATION USING LPBS
DOI:
https://doi.org/10.11113/jt.v78.9008Keywords:
Generalized hyperbolic distribution, portfolio optimizationAbstract
In recent years, several deoxyribonucleic acid (DNA)-based approaches have been developed for species identification including DNA sequencing. The search for motif or patterns in DNA sequences is important in many fields especially in biology. In this paper, a new particle swarm optimization (PSO) approach for discovering species-specific motifs was proposed. The new method named as Linear-PSO with Binary Search (LPBS) is developed to discover motifs of specific species through DNA sequences. This enhanced method integrates Linear-PSO and binary search technique to minimize the execution time and to increase the correctness in identifying the motif. In this study, two fragments samples of ‘mitochondrial cytochrome C oxidase subunit I’ (COI or COX1) were collected from the Genbank online database. DNA sequences for the first sample are fragments of COI for one species and the second samples are a complete COI from a different species. The genome of COI was used as a reference set and other DNA sequences were used as a comparison set. The results show that the LPBS algorithm is able to discover motifs of a species when using DNA sequences from the same fragment of COI.Â
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