• DocumentCode
    618000
  • Title

    Cellular automata for modeling protein folding using the HP model

  • Author

    Santos, Jose ; Villot, Pablo ; Dieguez, Martin

  • Author_Institution
    Dept. of Comput. Sci., Univ. of A Coruna, A Coruña, Spain
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    1586
  • Lastpage
    1593
  • Abstract
    We used cellular automata (CA) for the modeling of the temporal folding of proteins. Unlike the focus of the vast research already done on the direct prediction of the final folded conformations, we will model the temporal and dynamic folding process. The CA model defines how the amino acids interact through time to obtain a folded conformation. We employed the TIP model to represent the protein conformations in a lattice, we extended the classical CA models using artificial neural networks for their implementation, and we used evolutionary computing to automatically obtain the models by means of Differential Evolution. Moreover, the modeling of the folding provides the final protein conformation.
  • Keywords
    biology computing; cellular automata; evolutionary computation; molecular biophysics; molecular configurations; neural nets; proteins; TIP model; amino acids; artificial neural networks; cellular automata; classical CA model; differential evolution; dynamic folding process; evolutionary computing; final folded protein conformation prediction; protein folding modeling; temporal folding process; Amino acids; Artificial neural networks; Computational modeling; Lattices; Proteins; Sociology; Protein folding; cellular automata; differential evolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557751
  • Filename
    6557751