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
Link To Document :
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