Structural Bioinformatics and Computational Biochemistry, University of Oxford, South Parks Road, Oxford, UK.
Database (Oxford). 2010 Dec 17;2010:baq033. doi: 10.1093/database/baq033. Print 2010.
Molecular dynamics simulations can now routinely generate data sets of several hundreds of gigabytes in size. The ability to generate this data has become easier over recent years and the rate of data production is likely to increase rapidly in the near future. One major problem associated with this vast amount of data is how to store it in a way that it can be easily retrieved at a later date. The obvious answer to this problem is a database. However, a key issue in the development and maintenance of such a database is its sustainability, which in turn depends on the ease of the deposition and retrieval process. Encouraging users to care about meta-data is difficult and thus the success of any storage system will ultimately depend on how well used by end-users the system is. In this respect we suggest that even a minimal amount of metadata if stored in a sensible fashion is useful, if only at the level of individual research groups. We discuss here, a simple database system which we call 'Bookshelf', that uses python in conjunction with a mysql database to provide an extremely simple system for curating and keeping track of molecular simulation data. It provides a user-friendly, scriptable solution to the common problem amongst biomolecular simulation laboratories; the storage, logging and subsequent retrieval of large numbers of simulations. Download URL: http://sbcb.bioch.ox.ac.uk/bookshelf/
分子动力学模拟现在可以常规地生成数百千兆字节大小的数据。近年来，生成这种数据的能力变得更加容易，并且在不久的将来，数据生成的速度可能会迅速提高。与大量数据相关的一个主要问题是如何以一种可以在以后方便检索的方式存储它。这个问题的明显答案是数据库。然而，此类数据库的开发和维护中的一个关键问题是其可持续性，这反过来又取决于存储和检索过程的难易程度。鼓励用户关注元数据是困难的，因此任何存储系统的成功最终都取决于最终用户对系统的使用程度。在这方面，我们建议即使存储了少量有意义的元数据也是有用的，即使只是在单个研究小组的层面上。我们在这里讨论了一个简单的数据库系统，我们称之为“书架”（Bookshelf），它使用 Python 结合 MySQL 数据库，为生物分子模拟实验室中常见的问题，即大量模拟的存储、记录和后续检索，提供了一个用户友好的、可脚本化的解决方案。下载地址：http://sbcb.bioch.ox.ac.uk/bookshelf/
