Machine learning applications in macromolecular X-ray crystallography
CRYSTALLOGRAPHY REVIEWS(2021)
Abstract
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.
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Key words
Machine learning,big data,automation,macromolecular X-ray crystallography,synchrotron,structural biology
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