A distributed genetic algorithm for RNA secondary structure prediction

Author

Hendriks, Andrew ; Wiese, Kay C. ; Glen, Edward ; Deschenes, A.

Author_Institution

Inf. Technol., Simon Fraser Univ., Surrey, BC, Canada

Volume

1

fYear

2003

fDate

8-12 Dec. 2003

Firstpage

343

Abstract

This paper presents a new coarse-grained distributed genetic algorithm (GA) for the prediction of the secondary structure of RNA molecules, based largely on a serial permutation-based GA. The benefits of the distributed GA over our existing serial GA are analyzed and demonstrated. We also analyze the impact of the keep-best reproduction (KBR) and roulette wheel selection (STDS) GA replacement techniques. Finally, we verify the increase in convergence speed of our distributed GA. Tests was performed on 241 and 785 nucleotide sequences. Overall, the distributed GA is found to improve upon the serial GA performances, with a much more pronounced impact on the STDS selection strategy. There is also a notable acceleration in convergence speed.

Keywords

biology computing; genetic algorithms; macromolecules; molecular biophysics; GA replacement techniques; RNA molecules; RNA secondary structure prediction; coarse-grained distributed genetic algorithm; convergence speed; keep-best reproduction; nucleotide sequences; roulette wheel selection; selection strategy; serial permutation-based GA; Algorithm design and analysis; Amino acids; Cities and towns; Convergence; Genetic algorithms; Information technology; Performance analysis; RNA; Road transportation; Sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2003. CEC '03. The 2003 Congress on

Print_ISBN

0-7803-7804-0

Type

conf

DOI

10.1109/CEC.2003.1299596

Filename

1299596