A global grid for analysis of arthropod evolution. Stewart, C., A., Keller, R., Repasky, R., Hess, M., Hart, D., Müller, M., Sheppard, R., Wössner, U., Aumüller, M., Li, H., Berry, D., K., & Colbourne, J. In Proceedings - IEEE/ACM International Workshop on Grid Computing, pages 328-337, 2004. doi abstract bibtex Maximum likelihood analysis is a powerful technique for inferring evolutionary histories from genetic sequence data. During the fall of 2003, an international team of computer scientists, biologists, and computer centers created a global grid to analyze the evolution of hexapods (arthropods with six legs). We created a global grid of computers using systems located in eight countries, spread across six continents (every continent but Antarctica). This work was done as part of the SC03 HPC Challenge, and this project was given an HPC Challenge award for the "Most Distributed Application." More importantly, the creation of this computing grid enabled investigation of important questions regarding the evolution of arthropods - research that would not have otherwise been undertaken. Grid computing will thus lead directly to new scientific insights. © 2004 IEEE.
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title = {A global grid for analysis of arthropod evolution},
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year = {2004},
pages = {328-337},
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abstract = {Maximum likelihood analysis is a powerful technique for inferring evolutionary histories from genetic sequence data. During the fall of 2003, an international team of computer scientists, biologists, and computer centers created a global grid to analyze the evolution of hexapods (arthropods with six legs). We created a global grid of computers using systems located in eight countries, spread across six continents (every continent but Antarctica). This work was done as part of the SC03 HPC Challenge, and this project was given an HPC Challenge award for the "Most Distributed Application." More importantly, the creation of this computing grid enabled investigation of important questions regarding the evolution of arthropods - research that would not have otherwise been undertaken. Grid computing will thus lead directly to new scientific insights. © 2004 IEEE.},
bibtype = {inproceedings},
author = {Stewart, Craig A. and Keller, Rainer and Repasky, Richard and Hess, Matthias and Hart, David and Müller, Matthias and Sheppard, Ray and Wössner, Uwe and Aumüller, Martin and Li, Huian and Berry, Donald K. and Colbourne, John},
doi = {10.1109/GRID.2004.1},
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