GP challenge: evolving energy function for protein structure prediction
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Widera:2009:GPEM,
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author = "Pawel Widera and Jonathan M. Garibaldi and
Natalio Krasnogor",
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title = "GP challenge: evolving energy function for protein
structure prediction",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2010",
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volume = "11",
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number = "1",
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pages = "61--88",
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month = mar,
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keywords = "genetic algorithms, genetic programming, Protein
structure prediction, Protein energy function",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-009-9087-0",
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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.",
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notes = "Winner 2010 HUMIES GECCO 2010
",
- }
Genetic Programming entries for
Pawel Widera
Jonathan M Garibaldi
Natalio Krasnogor
Citations