A comprehensive survey on genetic algorithms for DNA motif prediction

Abstract Computational DNA motif discovery is important because it allows for speedy and cost effective analysis of sequences enriched with DNA motifs, performs large scale comparative studies, and tests hypotheses on biological problems. In this work, we provide a comprehensive survey on DNA motif discovery using genetic algorithm (GA). According to the ways of how the solution domain are encoded, we categorize existing GA-based motif discovery techniques into search for consensus and search by position (matrix). Within each category, we make distinctive algorithmic comparisons based on model representations, fitness functions, genetic operators, data post-processing, as well as the experimental results. Moreover, we discuss the strengths and weaknesses of different approaches with recommendations for practical use. This survey paper is useful as guideline for practitioners who would like to design GA solutions for DNA motif prediction in the future.

• Publication year

  2018

• Venue

  Information Sciences

• Publication date

  2018-10-01

• Fields of study

  Biology, Computer Science

• Identifiers
  DOI 10.1016/J.INS.2018.07.004
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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