A comprehensive survey on genetic algorithms for DNA motif prediction

Nung Kion Lee, Xi Li, Dianhui Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)25-43
Number of pages19
JournalInformation Sciences
Volume466
DOIs
Publication statusPublished - Oct 2018
Externally publishedYes

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