Incorporating Knowledge of Secondary Structures in a L-System-Based Encoding for Protein Folding

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Ochoa:2005:EA,
  author =       "Gabriela Ochoa and Gabi Escuela and 
                 Natalio Krasnogor",
  title =        "Incorporating Knowledge of Secondary Structures in a
                 L-System-Based Encoding for Protein Folding",
  booktitle =    "7th International Conference on Artificial Evolution
                 EA 2005",
  year =         "2005",
  editor =       "El-Ghazali Talbi and Pierre Liardet and 
                 Pierre Collet and Evelyne Lutton and Marc Schoenauer",
  volume =       "3871",
  series =       "Lecture Notes in Computer Science",
  pages =        "247--258",
  address =      "Lille, France",
  month =        oct # " 26-28",
  publisher =    "Springer",
  note =         "Revised Selected Papers",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-33589-4",
  URL =          "http://www.cs.stir.ac.uk/~goc/papers/LsysPFPEA05.pdf",
  DOI =          "doi:10.1007/11740698_22",
  size =         "12 pages",
  abstract =     "An encoding scheme for protein folding on lattice
                 models, inspired by parametric L-systems, was proposed.
                 The encoding incorporates problem domain knowledge in
                 the form of predesigned production rules that capture
                 commonly known secondary structures: alpha-helices and
                 beta-sheets. The ability of this encoding to capture
                 protein native conformations was tested using an
                 evolutionary algorithm as the inference procedure for
                 discovering L-systems. Results confirmed the
                 suitability of the proposed representation. It appears
                 that the occurrence of motifs and sub-structures is an
                 important component in protein folding, and these
                 sub-structures may be captured by a grammar-based
                 encoding. This line of research suggests novel and
                 compact encoding schemes for protein folding that may
                 have practical implications in solving meaningful
                 problems in biotechnology such as structure prediction
                 and protein folding.",
  notes =        "published 2006",
}

Genetic Programming entries for Gabriela Ochoa Gabi Escuela Natalio Krasnogor

Citations