A comprehensive survey on genetic algorithms for DNA motif prediction

被引:23
作者
Lee, Nung Kion [1 ]
Li, Xi [2 ]
Wang, Dianhui [3 ]
机构
[1] Univ Malaysia Sarawak, Fac Cognit Sci & Human Dev, Sarawak, Malaysia
[2] Australia Natl Univ, John Curtin Sch Med Res, Canberra, ACT, Australia
[3] La Trobe Univ Melbourne, Dept Comp Sci & Informat Technol, Melbourne, Vic, Australia
关键词
Genetic algorithm; DNA motif prediction; FACTOR-BINDING SITES; TRANSCRIPTIONAL REGULATORY ELEMENTS; COMPUTATIONAL IDENTIFICATION; INFORMATION-CONTENT; DISCOVERY; SPECIFICITY; REGIONS; SEQUENCES; PIPELINE; SIGNALS;
D O I
10.1016/j.ins.2018.07.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:25 / 43
页数:19
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