Name
Title | ||
|---|---|---|
Using computational grid capabilities to enhance the capability of an X-ray source for structural biology |
Abstract | ||
|---|---|---|
The Advanced Photon Source at Argonne National Laboratory enables structural biologists to perform state-of-the-art crystallography diffraction experiments with high-intensity X-rays. The data gathered during such experiments is used to determine the molecular structure of macromolecules to enhance, for example, the capabilities of modern drug design for basic and applied research. The steps involved in obtaining a complete structure are computationally intensive and require the proper adjustment of a considerable number of parameters that are not known a priori. Thus, it is advantageous to develop a computational infrastructure for solving the numerically complex problems quickly, in order to enable quasi-real-time information discovery and computational steering. Specifically, we propose that the time-consuming calculations be performed in a “computational grid” accessing a large number of state-of-the-art computational facilities. Furthermore, we envision that experiments could be conducted by researchers at their home institution via remote steering while a beamline technician performs the actual experiment; such an approach would be cost-efficient for the user. We conducted a case study involving multiple tasks of a structural biologist, including data acquisition, data reduction, solution of the phase problem, and calculation of the final result – an electron density map, which is subsequently used for modeling of the molecular structure. We developed a parallel program for the data reduction phase that reduces the turnaround time significantly. We also distributed the solution of the phase problem in order to obtain the resulting electron density map more quickly. We used the GUSTO testbed provided by the Globus metacomputing project as the source of the necessary state-of-the-art computational resources, including workstation clusters. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1023/A:1019036421819 | Cluster Computing |
Keywords | Field | DocType |
molecular structure,necessary state-of-the-art computational resource,electron density map,data acquisition,structural biology,computational infrastructure,x-ray source,state-of-the-art computational facility,computational steering,computational grid,phase problem,computational grid capability,structural biologist,data gathering,electron density,drug design,data reduction,real time,cost efficiency | Computer science,Parallel computing,Data acquisition,Phase problem,Computational science,Turnaround time,Metacomputing,Sequential algorithm,Grid,Computational steering,Distributed computing,Information discovery | Journal |
Volume | Issue | ISSN |
3 | 3 | 1573-7543 |
Citations | PageRank | References |
6 | 1.97 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gregor von Laszewski | 1 | 1795 | 157.85 |
| Mary L. Westbrook | 2 | 6 | 1.97 |
| Craig Barnes | 3 | 102 | 12.09 |
| Foster Ian | 4 | 22938 | 2663.24 |
| Edwin Westbrook | 5 | 92 | 7.24 |