Cinder: Keeping crystallographers App-y

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Rosa, Nick; Ristic, Marko; Marshall, Bevan ORCID ID icon; Newman, Janet ORCID ID icon


Journal Article

Acta Crystallographica Section F



The process of producing suitable crystals for X-ray diffraction analysis most often involves the setting up of hundreds (or thousands) of individual crystallisation trials, each of which must be repeatedly examined for crystals, or hints of crystallinity. Currently the only real way to address this bottleneck is to use an automated imager to capture images of the trials. However, the images still need to be assessed for crystals or other outcomes. Ideally there would exist some rapid and reliable machine analysis tool to translate the images into a quantitative result. However, as yet no such tool exists in wide usage, despite this being a well-recognised problem. One of the issues in creating robust automatic image analysis software is the lack of reliable data to be used to train machine learning algorithms. We have developed a mobile application, Cinder, which allows crystallisation images to be scored quickly on a smartphone or tablet. The Cinder scores are inserted into the appropriate table in a crystallisation database, and are immediately available to the user through a more sophisticated web interface allowing for more detailed analyses. We observed a sharp increase in the number of scored images after Cinder was released, which in turn provides more data for training machine learning tools.


Crystallisation, images, scoring, machine learning



Journal article - Refereed


Rosa, Nick; Ristic, Marko; Marshall, Bevan; Newman, Janet. Cinder: Keeping crystallographers App-y. Acta Crystallographica Section F. 2018; 74:410-418.

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