Literature DB >> 27173272

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

D Karaboga1, S Aslan2.   

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.

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Year:  2016        PMID: 27173272     DOI: 10.4238/gmr.15028645

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  2 in total

Review 1.  Review of Different Sequence Motif Finding Algorithms.

Authors:  Fatma A Hashim; Mai S Mabrouk; Walid Al-Atabany
Journal:  Avicenna J Med Biotechnol       Date:  2019 Apr-Jun

2.  A survey on deep learning in DNA/RNA motif mining.

Authors:  Ying He; Zhen Shen; Qinhu Zhang; Siguo Wang; De-Shuang Huang
Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

  2 in total

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