P-RnaPredict--a parallel evolutionary algorithm for RNA folding: effects of pseudorandom number quality.

Kay C Wiese; Andrew Hendriks; Alain Deschênes; Belgacem Ben Youssef

doi:10.1109/tnb.2005.853656

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P-RnaPredict--a parallel evolutionary algorithm for RNA folding: effects of pseudorandom number quality.

Kay C Wiese·Andrew Hendriks·Alain Deschênes·Belgacem Ben Youssef

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Abstract

This paper presents a fully parallel version of RnaPredict, a genetic algorithm (GA) for RNA secondary structure prediction. The research presented here builds on previous work and examines the impact of three different pseudorandom number generators (PRNGs) on the GA's performance. The three generators tested are the C standard library PRNG RAND, a parallelized multiplicative congruential generator (MCG), and a parallelized Mersenne Twister (MT). A fully parallel version of RnaPredict using the Message Passing Interface (MPI) was implemented on a 128-node Beowulf cluster. The PRNG comparison tests were performed with known structures whose sequences are 118, 122, 468, 543, and 556 nucleotides in length. The effects of the PRNGs are investigated and the predicted structures are compared to known structures. Results indicate that P-RnaPredict demonstrated good prediction accuracy, particularly so for shorter sequences.

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Algorithms Computer Simulation Information Storage and Retrieval Models, Chemical Models, Molecular Models, Statistical Nucleic Acid Conformation Numerical Analysis, Computer-Assisted RNA Sequence Analysis, RNA Software Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't

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Kay C Wiese, Andrew Hendriks, Alain Deschênes, Belgacem Ben Youssef. 2005. P-RnaPredict--a parallel evolutionary algorithm for RNA folding: effects of pseudorandom number quality.. https://doi.org/10.1109/tnb.2005.853656

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