Automating tasks in protein structure determination with the clipper python module.

Automating tasks in protein structure determination with the clipper python module.
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DOI:
10.1002/pro.3299
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发表时间:
2018-01
期刊:
Protein science : a publication of the Protein Society
影响因子:
--
通讯作者:
Agirre J
Agirre J
中科院分区:
其他
文献类型:
--
作者:
McNicholas S;Croll T;Burnley T;Palmer CM;Hoh SW;Jenkins HT;Dodson E;Cowtan K;Agirre J

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脚本编程语言提供了对复杂功能进行原型化的最快方法。那些具有类似人类语言的语法和语法的代码也极大地增强了所生成的源代码的可维护性。此外,强大的、独立于机器的脚本语言与为每种计算机架构量身定制的二进制库相结合,使程序能够摆脱传统上与脚本相关的效率的严格界限。在目前的工作中,我们描述了一个有效的C++晶体库,如Clipper可以包装,适应和推广使用晶体和电子冷冻显微镜应用程序,脚本与Python语言。我们还将强调自动化的最佳实践,说明如何使用这个新的Python模块实现这一点。
Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine‐independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo‐microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module.
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