Automating tasks in protein structure determination with the clipper python module.
Stuart McNicholasTristan CrollTom BurnleyColin M PalmerSoon Wen HohHuw T JenkinsEleanor DodsonKathryn D CowtanJon AgirrePublished in: Protein science : a publication of the Protein Society (2017)
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.
Keyphrases
- autism spectrum disorder
- high resolution
- endothelial cells
- deep learning
- healthcare
- primary care
- public health
- working memory
- single molecule
- high throughput
- induced pluripotent stem cells
- ionic liquid
- optical coherence tomography
- machine learning
- molecularly imprinted
- amino acid
- protein protein
- solid phase extraction