Classifying Protein Segments as Transmembrane Domains Using Architecture-Altering Operations in Genetic Programming   [GP]

by

Koza, J., R. and Andre, D.

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Info: Advances in Genetic Programming 2, 1996, p. 155-176
Keywords:genetic algorithms, genetic programming
Abstract:
The biological theory of gene duplication, concerning how new structures and new behaviors are created in living things, is brought to bear on the problem of automated architecture discovery in genetic programming. [GP] Using architecture-altering operations patterned after naturally-occurring gene duplication, genetic programming [GP] is used to evolve a computer program to classify a given protein segment as being a transmembrane domain or non-transmembrane area of the protein. The out-of-sample error rate for the best genetically-evolved program achieved was slightly better than that of previously-reported human-written algorithms for this problem. This is an instance of an automated machine learning algorithm [ML] rivaling a human-written algorithm for a problem.
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BibTex:
@InCollection{koza:1996:aigp2,
  author =       "John R. Koza and David Andre",
  title =        "Classifying Protein Segments as Transmembrane Domains
                 Using Architecture-Altering Operations in Genetic
                 Programming",
  booktitle =    "Advances in Genetic Programming 2",
  publisher =    "MIT Press",
  year =         "1996",
  editor =       "Peter J. Angeline and K. E. {Kinnear, Jr.}",
  pages =        "155--176",
  chapter =      "8",
  address =      "Cambridge, MA, USA",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-262-01158-1",
  abstract =     "The biological theory of gene duplication, concerning
                 how new structures and new behaviors are created in
                 living things, is brought to bear on the problem of
                 automated architecture discovery in genetic
                 programming. Using architecture-altering operations
                 patterned after naturally-occurring gene duplication,
                 genetic programming is used to evolve a computer
                 program to classify a given protein segment as being a
                 transmembrane domain or non-transmembrane area of the
                 protein. The out-of-sample error rate for the best
                 genetically-evolved program achieved was slightly
                 better than that of previously-reported human-written
                 algorithms for this problem. This is an instance of an
                 automated machine learning algorithm rivaling a
                 human-written algorithm for a problem.",
}