Distributed computing for macromolecular crystallography

被引:61
作者
Krissinel, Evgeny [1 ]
Uski, Ville [1 ]
Lebedev, Andrey [1 ]
Winn, Martyn [1 ]
Ballard, Charles [1 ]
机构
[1] Rutherford Appleton Lab, STFC, Sci Comp Dept, Didcot OX11 0FA, Oxon, England
来源
ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY | 2018年 / 74卷
基金
英国生物技术与生命科学研究理事会; 欧盟地平线“2020”;
关键词
crystallographic computing; distributed computing; data and project management; web services; computational cloud; MOLECULAR-REPLACEMENT; CRYSTAL-STRUCTURES; SOFTWARE; GRAPHICS; PIPELINE;
D O I
10.1107/S2059798317014565
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Modern crystallographic computing is characterized by the growing role of automated structure-solution pipelines, which represent complex expert systems utilizing a number of program components, decision makers and databases. They also require considerable computational resources and regular database maintenance, which is increasingly more difficult to provide at the level of individual desktop-based CCP4 setups. On the other hand, there is a significant growth in data processed in the field, which brings up the issue of centralized facilities for keeping both the data collected and structure-solution projects. The paradigm of distributed computing and data management offers a convenient approach to tackling these problems, which has become more attractive in recent years owing to the popularity of mobile devices such as tablets and ultra-portable laptops. In this article, an overview is given of developments by CCP4 aimed at bringing distributed crystallographic computations to a wide crystallographic community.
引用
收藏
页码:143 / 151
页数:9
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