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BioSimGrid: Grid-enabled biomolecular simulation data storage and analysis

机译:BioSimGrid:支持网格的生物分子模拟数据存储和分析

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In computational biomolecular research, large amounts of simulation data are generated to capture the motion of proteins. These massive simulation data can be analysed in a number of ways to reveal the biochemical properties of the proteins. However, the legacy way of storing these data (usually in the laboratory where the simulations have been run) often hinders a wider sharing and easier cross-comparison of simulation results. The data is commonly encoded in a way specific to the simulation package that produced the data and can only be analysed with tools developed specifically for that simulation package. The BioSimGrid platform seeks to provide a solution to these challenges by exploiting the potential of the Grid in facilitating data sharing. By using BioSimGrid either in a scripting or web environment, users can deposit their data and reuse it for analysis. BioSimGrid tools manage the multiple storage locations transparently to the users and provide a set of retrieval and analysis tools for processing the data in a convenient and efficient manner. This paper details the usage and implementation of BioSimGrid using a combination of commercial databases, the Storage Resource Broker and Python scripts, gluing the building blocks together. It introduces a case study of how BioSimGrid can be used for better storage, retrieval and analysis of biomolecular simulation data.
机译:在计算生物分子研究中,生成了大量的模拟数据来捕获蛋白质的运动。这些大量的模拟数据可以通过多种方式进行分析,以揭示蛋白质的生化特性。但是,存储这些数据的传统方式(通常在运行模拟的实验室中)通常会阻碍更广泛的共享和更容易的交叉比较模拟结果。数据通常以特定于生成数据的模拟包的方式进行编码,并且只能使用专门为该模拟包开发的工具进行分析。 BioSimGrid平台旨在通过利用Grid在促进数据共享方面的潜力来提供针对这些挑战的解决方案。通过在脚本或Web环境中使用BioSimGrid,用户可以保存其数据并将其重新用于分析。 BioSimGrid工具对用户透明地管理多个存储位置,并提供一组检索和分析工具,以方便,高效的方式处理数据。本文通过结合商业数据库,存储资源代理和Python脚本,详细介绍了BioSimGrid的用法和实现,并将构建模块粘合在一起。本文介绍了如何利用BioSimGrid更好地存储,检索和分析生物分子模拟数据的案例研究。

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