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Protein simulation data in the relational model

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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.

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Authors and Affiliations

  1. Biomedical and Health Informatics Program, University of Washington, Box 355013, Seattle, WA, 98195-5013, USA

    Andrew M. Simms & Valerie Daggett

  2. Bioengineering, University of Washington, Box 355013, Seattle, WA, 98195-5013, USA

    Valerie Daggett

Authors
  1. Andrew M. Simms
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  2. Valerie Daggett
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Correspondence to Valerie Daggett.

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Simms, A.M., Daggett, V. Protein simulation data in the relational model. J Supercomput 62, 150–173 (2012). https://doi.org/10.1007/s11227-011-0692-3

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  • DOI: https://doi.org/10.1007/s11227-011-0692-3

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