• DocumentCode
    3469319
  • Title

    Evolutionary molecular structure determination using Grid-enabled data mining

  • Author

    Green, Mark L. ; Miller, Russ

  • Author_Institution
    Dept. of Comput. Sci. & Eng., State Univ. of New York, USA
  • fYear
    2004
  • fDate
    19-22 April 2004
  • Firstpage
    328
  • Lastpage
    335
  • Abstract
    A new computational framework is developed for the evolutionary determination of molecular crystal structures using the shake-and-bake methodology. Genetic algorithms are performed on the SnB results of known structures in order to optimize critical parameters of the program. The determination of efficient SnB input parameters can significantly reduce the time required to solve unknown molecular structures. Further, the Grid-enabled data mining approach that we introduce is able to exploit computational cycles that would otherwise go unused.
  • Keywords
    X-ray crystallography; data mining; genetic algorithms; grid computing; molecular configurations; Grid-enabled data mining; computational cycles; evolutionary determination; genetic algorithms; molecular crystal structures; optimization; shake-and-bake methodology; Application software; Atomic measurements; Computer science; Crystallography; Data engineering; Data mining; Diffraction; Fourier transforms; Genetic algorithms; Grid computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing and the Grid, 2004. CCGrid 2004. IEEE International Symposium on
  • Print_ISBN
    0-7803-8430-X
  • Type

    conf

  • DOI
    10.1109/CCGrid.2004.1336584
  • Filename
    1336584