Machine learning applications in macromolecular X-ray crystallography
Machine learning applications in macromolecular X-ray crystallography
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DOI：
10.1080/0889311x.2021.1982914
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发表时间：
2021-04
影响因子：
3
通讯作者：
M. Vollmar;G. Evans
中科院分区：
文献类型：
--
作者：
M. Vollmar;G. Evans
经过半个多世纪的发展，机器学习和人工智能总体上正在进入一个真正令人兴奋的时代，在商业和研究领域得到广泛应用。在x射线晶体学及其在结构生物学中的应用中，机器学习正在专家和自动化系统中找到一个家，正在预测实验和数据分析结果，正在预测晶体是否可以生长，甚至产生大分子结构。这篇综述提供了人工智能和机器学习的历史视角，提供了人工智能在晶体学中的应用的介绍和指导，并总结了人工智能目前如何影响大分子晶体学的热门例子。
After more than half a century of evolution, machine learning and artificial intelligence, in general, are entering a truly exciting era of broad application in commercial and research sectors. In X-ray crystallography, and its application to structural biology, machine learning is finding a home within expert and automated systems, is forecasting experiment and data analysis outcomes, is predicting whether crystals can be grown and even generating macromolecular structures. This review provides a historical perspective on AI and machine learning, offers an introduction and guide to its application in crystallography and concludes with topical examples of how it is currently influencing macromolecular crystallography.