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tural biologists to perform state-of-the-art crystallography diraction 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 inten-sive 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 infras-tructure for solving the numerically complex problems quickly, in order to enable quasi-real-time information discovery and computational steering. Specically, we propose that the time-consuming calculations be performed in a \computational grid " accessing a large number of state-of-the-art computational facilities. Further-more, we envision that experiments could be conducted by researchers at their home institution via remote steering while a beamline technician performs the actual ex-periment; such an approach would be cost-eÆcient 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 cal-culation of the nal 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 signicantly. 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 Corresponding author