Discovery of conserved regions in DNA sequences by Artificial Bee Colony (ABC) algorithm based methods

• Published in: Natural computing Vol. 18; no. 2; pp. 333 - 350
• Main Authors: Karaboga, Dervis, Aslan, Selcuk
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2019; Springer Nature B.V
• Subjects: Artificial Intelligence; Avalanches; Bioinformatics; Complex Systems; Computer Science; Deoxyribonucleic acid; DNA; Evolutionary Biology; Gene sequencing; Parallel processing; Processor Architectures; Regulatory mechanisms (biology); Search algorithms; Swarm intelligence; Theory of Computation; Artificial Bee Colony algorithm; Metaheuristics; Motif discovery
• ISSN: 1567-7818; 1572-9796
• DOI: 10.1007/s11047-018-9674-1

The conserved regions between genomic sequences extracted from the different species give important information about the complex regulatory mechanisms of the transcription and translation processes. However, identification of these regulatory regions that are short DNA segments and called motifs is a major challenge in bioinformatics. With the avalanche of the newly sequenced genomic data and our evolving understanding of the characteristics of the regulatory mechanisms, there is still a need for developing fast and accurate motif discovery techniques or considerably refinement on the existing models. In this paper, we presented two different Artificial Bee Colony algorithm based motif discovery techniques and investigated their serial and parallelized implementations. Experimental studies on the three real data sets showed that the proposed methods outperformed other metaheuristics in terms of similarity values of the predicted motifs.