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© Oxford University Press

An annealing mutation operator in the genetic algorithms for RNA folding

Bruce A. Shapiro and Jin Chu Wu 1

Image Processing Section, Laboratory of Mathematical Biology, Division of Basic Sciences, National Cancer Institute, Frederick Cancer Research and Development Center, National Institutes of Health Bldg 469, Rm 150, Frederick, MD 21702, USA
1Frederick Biomedical Supercomputing Center, SAIC Frederick/LMB, NCI-FCRDC, Frederick, MD 21702, USA

An annealing mutation operator in the genetic algorithms (GA) for RNA folding on a MasPar MP-2 has been designed. The mutation probability descends along a hyperbola with respect to the size of the secondary structure, hence the total number of mutations at each generation drops linearly. Especially for long sequences with thousands of nucleotides as opposed to hundreds of nucleotides, the new mutation operator can make the distribution of free energies over all processors on MasPar MP-2 converge only after hundreds of generations. Based upon this new mutation operator, a technique to terminate the GA is also developed. The new mutation operator runs very efficiently. Some variations of the annealing mutation operator are also discussed.

Received on July 3, 1995; accepted on February 2, 1996

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