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

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  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


                 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.


                 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