Genetic Programming for Improved Data Mining: An Application to the Biochemistry of Protein Interactions

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{raymer:1996:GPidm:bpi,
  author =       "M. L. Raymer and W. F. Punch and E. D. Goodman and 
                 L. A. Kuhn",
  title =        "Genetic Programming for Improved Data Mining: An
                 Application to the Biochemistry of Protein
                 Interactions",
  booktitle =    "Genetic Programming 1996: Proceedings of the First
                 Annual Conference",
  editor =       "John R. Koza and David E. Goldberg and 
                 David B. Fogel and Rick L. Riolo",
  year =         "1996",
  month =        "28--31 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  pages =        "375--380",
  address =      "Stanford University, CA, USA",
  publisher =    "MIT Press",
  URL =          "http://garage.cse.msu.edu/papers/GARAGe96-04-01.pdf",
  URL =          "http://cognet.mit.edu/sites/default/files/books/9780262315876/pdfs/9780262315876_chap51.pdf",
  URL =          "http://cognet.mit.edu/library/books/view?isbn=0262611279",
  size =         "6 pages",
  abstract =     "We have previously shown how a genetic algorithm (GA)
                 can be used to perform `data mining' the discovery of
                 particular/important data within large datasets, by
                 finding optimal data classifications using known
                 examples. However, these approaches, while successful,
                 limited data relationships to those that were `fixed'
                 before the GA run. We report here on an extension of
                 our previous work, substituting a genetic program (GP)
                 for a GA. The GP could optimise data classification, as
                 did the GA, but could also determine the functional
                 relationships among the features. This gave improved
                 performance and new information on important
                 relationships among features. We discuss the overall
                 approach, and compare the effectiveness of the GA vs.
                 GP on a biochemistry problem, the determination of the
                 involvement of bound water molecules in protein
                 interactions.",
  notes =        "GP-96 Also available as TR GARAGe96-04-01",
}

Genetic Programming entries for Michael L Raymer William F Punch Erik Goodman L A Kuhn

Citations