• DocumentCode
    785547
  • Title

    Mining residue contacts in proteins using local structure predictions

  • Author

    Zaki, Mohammed J. ; Jin, Shan ; Bystroff, Chris

  • Author_Institution
    Comput. Sci. Dept., Rensselaer Polytech. Inst., Troy, NY, USA
  • Volume
    33
  • Issue
    5
  • fYear
    2003
  • Firstpage
    789
  • Lastpage
    801
  • Abstract
    In this paper we develop data mining techniques to predict 3D contact potentials among protein residues (or amino acids) based on the hierarchical nucleation-propagation model of protein folding. We apply a hybrid approach, using a hidden Markov model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.
  • Keywords
    biology computing; data mining; hidden Markov models; molecular biophysics; molecular configurations; physiological models; proteins; HMM; association mining; contact potential discovery; folding initiation site extraction; hidden Markov model; hierarchical nucleation-propagation model; local structure predictions; protein folding; protein residue contact mining; Amino acids; Bioinformatics; Data mining; Databases; Genomics; Hidden Markov models; Pattern analysis; Predictive models; Protein engineering; Sequences;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/TSMCB.2003.816916
  • Filename
    1232716