NAMD2: greater scalability for parallel molecular dynamics
Journal of Computational Physics - Special issue on computational molecular biophysics
Large scale distributed data repository: design of a molecular dynamics trajectory database
Future Generation Computer Systems
On-Line Analytical Processing on Large Databases Managed by Computational Grids
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
Performance engineering in data Grids: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
The design and implementation of Grid database services in OGSA-DAI: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Dynamically Deploying Web Services on a Grid using Dynasoar
ISORC '06 Proceedings of the Ninth IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing
BioSimGrid: grid-enabled biomolecular simulation data storage and analysis
Future Generation Computer Systems - Collaborative and learning applications of grid technology
Distributed data mining services leveraging WSRF
Future Generation Computer Systems - Special section: Data mining in grid computing environments
Grid-enabling data mining applications with DataMiningGrid: An architectural perspective
Future Generation Computer Systems
Data Mining in Grid Computing Environments
Data Mining in Grid Computing Environments
ISBMDA'05 Proceedings of the 6th International conference on Biological and Medical Data Analysis
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The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories - this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.