Research Article

A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences

Published: April 27, 2016
Genet. Mol. Res. 15(2): gmr8645 DOI: https://doi.org/10.4238/gmr.15028645
Cite this Article:
(2016). A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences. Genet. Mol. Res. 15(2): gmr8645. https://doi.org/10.4238/gmr.15028645
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Abstract

The great majority of biological sequences share significant similarity with other sequences as a result of evolutionary processes, and identifying these sequence similarities is one of the most challenging problems in bioinformatics. In this paper, we present a discrete artificial bee colony (ABC) algorithm, which is inspired by the intelligent foraging behavior of real honey bees, for the detection of highly conserved residue patterns or motifs within sequences. Experimental studies on three different data sets showed that the proposed discrete model, by adhering to the fundamental scheme of the ABC algorithm, produced competitive or better results than other metaheuristic motif discovery techniques.

The great majority of biological sequences share significant similarity with other sequences as a result of evolutionary processes, and identifying these sequence similarities is one of the most challenging problems in bioinformatics. In this paper, we present a discrete artificial bee colony (ABC) algorithm, which is inspired by the intelligent foraging behavior of real honey bees, for the detection of highly conserved residue patterns or motifs within sequences. Experimental studies on three different data sets showed that the proposed discrete model, by adhering to the fundamental scheme of the ABC algorithm, produced competitive or better results than other metaheuristic motif discovery techniques.

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