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

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)...

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Bibliographic Details
Published inGenetics and molecular research Vol. 15; no. 2
Main Authors Karaboga, D., Aslan, S.
Format Journal Article
LanguageEnglish
Published Brazil 01.01.2016
Subjects
Algorithms
Amino Acid Motifs
Apis mellifera
Binding Sites
Conserved Sequence
Humans
Models, Genetic
Promoter Regions, Genetic
Protein Binding
Transcription Factors - chemistry
Transcription Factors - metabolism
Transcriptional Activation
Yeasts - genetics
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ISSN1676-5680
1676-5680
DOI10.4238/gmr.15028645

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Summary: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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ISSN:1676-5680
1676-5680
DOI:10.4238/gmr.15028645