Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics: Evolutionary Algorithms for Bioinformatics
Abstract
Since genetic algorithm was proposed by John Holland (Holland J. H., 1975) in the early 1970s, the study of evolutionary algorithm has emerged as a popular research field (Civicioglu & Besdok, 2013). Researchers from various scientific and engineering disciplines have been digging into this field, exploring the unique power of evolutionary algorithms (Hadka & Reed, 2013). Many applications have been successfully proposed in the past twenty years. For example, mechanical design (Lampinen & Zelinka, 1999), electromagnetic optimization (Rahmat-Samii & Michielssen, 1999), environmental protection (Bertini, Felice, Moretti, & Pizzuti, 2010), finance (Larkin & Ryan, 2010), musical orchestration (Esling, Carpentier, & Agon, 2010), pipe routing (Furuholmen, Glette, Hovin, & Torresen, 2010), and nuclear reactor core design (Sacco, Henderson, Rios-Coelho, Ali, & Pereira, 2009). In particular, its function optimization capability was highlighted (Goldberg & Richardson, 1987) because of its high adaptability to different function landscapes, to which we cannot apply traditional optimization techniques (Wong, Leung, & Wong, 2009). Here we review the applications of evolutionary algorithms in bioinformatics.
Keywords
Cite
@article{arxiv.1508.00468,
title = {Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics: Evolutionary Algorithms for Bioinformatics},
author = {Ka-Chun Wong},
journal= {arXiv preprint arXiv:1508.00468},
year = {2015}
}