A genetic approach for building different alphabets for peptide and protein classification

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@Article{Nanni:2008:BMCbi,
  author =       "Loris Nanni and Alessandra Lumini",
  title =        "A genetic approach for building different alphabets
                 for peptide and protein classification",
  journal =      "BMC Bioinformatics",
  volume =       "9",
  year =         "2008",
  number =       "1",
  pages =        "45",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1471-2105",
  URL =          "http://www.biomedcentral.com/1471-2105/9/45",
  DOI =          "doi:10.1186/1471-2105-9-45",
  abstract =     "BACKGROUND:

                 In this paper, it is proposed an optimization approach
                 for producing reduced alphabets for peptide
                 classification, using a Genetic Algorithm. The
                 classification task is performed by a multi-classifier
                 system where each classifier (Linear or Radial Basis
                 function Support Vector Machines) is trained using
                 features extracted by different reduced alphabets. Each
                 alphabet is constructed by a Genetic Algorithm whose
                 objective function is the maximization of the area
                 under the ROC-curve obtained in several classification
                 problems.

                 RESULTS:

                 The new approach has been tested in three peptide
                 classification problems: HIV-protease, recognition of
                 T-cell epitopes and prediction of peptides that bind
                 human leukocyte antigens. The tests demonstrate that
                 the idea of training a pool classifiers by reduced
                 alphabets, created using a Genetic Algorithm, allows an
                 improvement over other state-of-the-art feature
                 extraction methods.

                 CONCLUSION:

                 The validity of the novel strategy for creating reduced
                 alphabets is demonstrated by the performance
                 improvement obtained by the proposed approach with
                 respect to other reduced alphabets-based methods in the
                 tested problems.",
  notes =        "\cite{Nanni201043} says its on GP",
  pubmedid =     "18218100",
}

Genetic Programming entries for Loris Nanni Alessandra Lumini

Citations