Evolving L-Systems to Capture Protein Structure Native Conformations

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

  author =       "Gabi Escuela and Gabriela Ochoa and 
                 Natalio Krasnogor",
  editor =       "Maarten Keijzer and Andrea Tettamanzi and 
                 Pierre Collet and Jano I. {van Hemert} and Marco Tomassini",
  title =        "Evolving L-Systems to Capture Protein Structure Native
  booktitle =    "Proceedings of the 8th European Conference on Genetic
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3447",
  year =         "2005",
  address =      "Lausanne, Switzerland",
  month =        "30 " # mar # " - 1 " # apr,
  organisation = "EvoNet",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-25436-6",
  pages =        "74--84",
  URL =          "http://www.cs.nott.ac.uk/~nxk/PAPERS/LsysPSP05.pdf",
  DOI =          "doi:10.1007/b107383",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  abstract =     "A protein is a linear chain of amino acids, that under
                 certain physical conditions, folds into a unique
                 functional structure, called its native state or
                 tertiary structure. In this state, proteins show
                 repeated substructures like alpha helices and beta
                 sheets. This observation suggests that native
                 structures may be captured by the formalism known as
                 Lindenmayer systems (L-systems). In this paper an
                 evolutionary algorithm is used as the inference
                 procedure for folded structures under the HP model in
                 2D lattices. The EA searches in the space of possible
                 L-systems which are then executed to obtain the
                 phenotype, thus our approach is close to that of
                 Grammatical Evolution. The problem is to find a set of
                 rewriting rules that represents a target native
                 structure on the selected lattice model. The proposed
                 approach has produced promising results for short
                 sequences under the 2D square lattice. Thus the
                 foundations are set for a novel encoding based on
                 L-systems for evolutionary approaches to both the
                 Protein Structure Prediction and Inverse Folding
  notes =        "Part of \cite{keijzer:2005:GP} EuroGP'2005 held in
                 conjunction with EvoCOP2005 and EvoWorkshops2005",

Genetic Programming entries for Gabi Escuela Gabriela Ochoa Natalio Krasnogor