GP challenge: evolving energy function for protein structure prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Pawel Widera and Jonathan M. Garibaldi and 
                 Natalio Krasnogor",
  title =        "GP challenge: evolving energy function for protein
                 structure prediction",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2010",
  volume =       "11",
  number =       "1",
  pages =        "61--88",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Protein
                 structure prediction, Protein energy function",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-009-9087-0",
  abstract =     "One of the key elements in protein structure
                 prediction is the ability to distinguish between good
                 and bad candidate structures. This distinction is made
                 by estimation of the structure energy. The energy
                 function used in the best state-of-the-art automatic
                 predictors competing in the most recent CASP (Critical
                 Assessment of Techniques for Protein Structure
                 Prediction) experiment is defined as a weighted sum of
                 a set of energy terms designed by experts. We
                 hypothesised that combining these terms more freely
                 will improve the prediction quality. To test this
                 hypothesis, we designed a genetic programming algorithm
                 to evolve the protein energy function. We compared the
                 predictive power of the best evolved function and a
                 linear combination of energy terms featuring weights
                 optimised by the Nelder-Mead algorithm. The GP based
                 optimisation outperformed the optimised linear
                 function. We have made the data used in our experiments
                 publicly available in order to encourage others to
                 further investigate this challenging problem by using
                 GP and other methods, and to attempt to improve on the
                 results presented here.",
  notes =        "Winner 2010 HUMIES GECCO 2010

Genetic Programming entries for Pawel Widera Jonathan M Garibaldi Natalio Krasnogor