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Title: Protein simulation data in the relational model.
Authors: Simms, Andrew; Daggett, Valerie
Abstract: High performance computing is leading to unprecedented volumes of data. Relational databases offer a robust and scalable model for storing and analyzing scientific data. However, these features do not come without a cost-significant design effort is required to build a functional and efficient repository. Modeling protein simulation data in a relational database presents several challenges: The data captured from individual simulations are large, multidimensional, and must integrate with both simulation software and external data sites. Here, we present the dimensional design and relational implementation of a comprehensive data warehouse for storing and analyzing molecular dynamics simulations using SQL Server.
Subjects: HIGH performance computing; SQL; RELATIONAL databases; COMPUTER simulation; SIMULATION methods & models
Publication: Journal of Supercomputing, 2012, Vol 62, Issue 1, p150
ISSN: 0920-8542
Publication type: Academic Journal
DOI: 10.1007/s11227-011-0692-3

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Protein simulation data in the relational model.