NDLI: A distributed genetic algorithm for RNA secondary structure prediction

Content Provider	IEEE Xplore Digital Library
Author	Hendriks, A. Wiese, K.C. Glen, E. Deschenes, A.
Copyright Year	2003
Description	Author affiliation: Inf. Technol., Simon Fraser Univ., Surrey, BC, Canada (Hendriks, A.; Wiese, K.C.; Glen, E.; Deschenes, A.)
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.
Sponsorship	Air Force Iffice of Sci. Res. Asian Office of Aerospace Res and Development Army Res. Office - Far East CISCO Evoluationary Programming Soc. IEE Inst. of Engineers, Australia IEEE Neural Networks Soc. Univ. of New South Wales
Starting Page	343
Ending Page	350
File Size	525984
Page Count	8
File Format	PDF
ISBN	0780378040
DOI	10.1109/CEC.2003.1299596
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms RNA Sequences Convergence Amino acids Information technology Cities and towns Road transportation Algorithm design and analysis Performance analysis
Content Type	Text
Resource Type	Article

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