• DocumentCode
    2915759
  • Title

    A multi-objective genetic algorithm for the Protein Structure Prediction

  • Author

    Chamorro, Alfonso E Márquez ; Divina, Federico ; Aguilar-Ruiz, Jesús S. ; Cortés, Gualberto Asencio

  • Author_Institution
    Sch. of Eng., Pablo de Olavide Univ., Seville, Spain
  • fYear
    2011
  • fDate
    22-24 Nov. 2011
  • Firstpage
    1086
  • Lastpage
    1090
  • Abstract
    The Protein Structure Prediction (PSP) problem consists of predicting the structure of a protein from its amino acids sequence, and have received much attention lately. In fact, being able to predict the structure of a protein, would allow to know the function of the protein. In this paper, we propose a multi-objective evolutionary algorithm for the PSP problem. The prediction model consists of a set of rules that determine possible contacts between amino acids. Such rules are based on four specific amino acid properties, which are involved in the folding process: hydrophobicity, polarity, net charge and residue size. In order to increase the interpretability of the results, rules are organized in a 20 × 20 matrix where each cell contains the specific rules for a possible pair of residues. The high accuracy values obtained confirm the validity of our proposal.
  • Keywords
    biology computing; genetic algorithms; hydrophobicity; proteins; amino acids sequence; folding process; hydrophobicity; multiobjective evolutionary algorithm; multiobjective genetic algorithm; net charge; polarity; protein structure prediction; residue size; Accuracy; Algorithm design and analysis; Amino acids; Optimization; Prediction algorithms; Protein engineering; Proteins; Amino Acid Properties; Contact Map; Evolutionary Computation; Multi-objective Optimization; Protein Structure Prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on
  • Conference_Location
    Cordoba
  • ISSN
    2164-7143
  • Print_ISBN
    978-1-4577-1676-8
  • Type

    conf

  • DOI
    10.1109/ISDA.2011.6121803
  • Filename
    6121803