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A massively parallel genetic algorithm for RNA secondary structure prediction

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Abstract

We present a new method for predicting RNA secondary structure based on a genetic algorithm. The algorithm is designed to run on a massively parallel SIMD computer. Statistical analysis shows that the program performs well when compared to a dynamic programming algorithm used to solve the same problem. The program has also pointed out a long-standing simplification in the implementation of the original dynamic programming algorithm that sometimes causes it not to find the optimal secondary structure.

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Authors and Affiliations

  1. Image Processing Section, Laboratory of Mathematical Biology, Division of Cancer Biology, Diagnosis and Centers, National Cancer Institute, Bldg. 469, Rm. 150, 21702, Frederick, MD

    Bruce A. Shapiro

  2. Frederick Cancer Research and Development Center, National Institutes of Health, Bldg. 469, Rm. 150, 21702, Frederick, MD

    Bruce A. Shapiro

  3. Frederick Biomedical Supercomputer Center, PRI/DynCorp, NCI/FCRDC, 21702, Frederick, MD

    Joseph Navetta

Authors
  1. Bruce A. Shapiro
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  2. Joseph Navetta
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Shapiro, B.A., Navetta, J. A massively parallel genetic algorithm for RNA secondary structure prediction. J Supercomput 8, 195–207 (1994). https://doi.org/10.1007/BF01204728

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  • DOI: https://doi.org/10.1007/BF01204728

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