Literature DB >> 29969104

Cinder: keeping crystallographers app-y.

Nicholas Rosa1, Marko Ristic1, Bevan Marshall1, Janet Newman1.   

Abstract

The process of producing suitable crystals for X-ray diffraction analysis most often involves the setting up of hundreds (or thousands) of individual crystallization 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 recognized problem. One of the issues in creating robust automatic image-analysis software is the lack of reliable data for training machine-learning algorithms. Here, a mobile application, Cinder, has been developed which allows crystallization images to be scored quickly on a smartphone or tablet. The Cinder scores are inserted into the appropriate table in a crystallization database and are immediately available to the user through a more sophisticated web interface, allowing more detailed analyses. A sharp increase in the number of scored images was observed after Cinder was released, which in turn provides more data for training machine-learning tools.

Keywords:  Cinder; crystallization; images; machine learning; mobile apps; scoring

Mesh:

Year:  2018        PMID: 29969104      PMCID: PMC6038447          DOI: 10.1107/S2053230X18008038

Source DB:  PubMed          Journal:  Acta Crystallogr F Struct Biol Commun        ISSN: 2053-230X            Impact factor:   1.056


  9 in total

1.  Computational analysis of crystallization trials.

Authors:  Glen Spraggon; Scott A Lesley; Andreas Kreusch; John P Priestle
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2002-10-21

2.  Automatic classification and pattern discovery in high-throughput protein crystallization trials.

Authors:  Christian Cumbaa; Igor Jurisica
Journal:  J Struct Funct Genomics       Date:  2005

3.  Improved classification of crystallization images using data fusion and multiple classifiers.

Authors:  Samarasena Buchala; Julie C Wilson
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2008-07-17

4.  Crystallization reports are the backbone of Acta Cryst. F, but do they have any spine?

Authors:  Janet Newman; Denis R Burton; Sofia Caria; Sebastien Desbois; Christine L Gee; Vincent J Fazio; Marc Kvansakul; Bevan Marshall; Grant Mills; Viviane Richter; Shane A Seabrook; Mingbo Wu; Thomas S Peat
Journal:  Acta Crystallogr Sect F Struct Biol Cryst Commun       Date:  2013-06-30

5.  What's in a drop? Correlating observations and outcomes to guide macromolecular crystallization experiments.

Authors:  Joseph R Luft; Jennifer R Wolfley; Edward H Snell
Journal:  Cryst Growth Des       Date:  2011-03-02       Impact factor: 4.076

6.  On the need for an international effort to capture, share and use crystallization screening data.

Authors:  Janet Newman; Evan E Bolton; Jochen Müller-Dieckmann; Vincent J Fazio; D Travis Gallagher; David Lovell; Joseph R Luft; Thomas S Peat; David Ratcliffe; Roger A Sayle; Edward H Snell; Kerry Taylor; Pascal Vallotton; Sameer Velanker; Frank von Delft
Journal:  Acta Crystallogr Sect F Struct Biol Cryst Commun       Date:  2012-02-15

7.  Lessons from ten years of crystallization experiments at the SGC.

Authors:  Jia Tsing Ng; Carien Dekker; Paul Reardon; Frank von Delft
Journal:  Acta Crystallogr D Struct Biol       Date:  2016-01-22       Impact factor: 7.652

8.  Establishing a training set through the visual analysis of crystallization trials. Part I: approximately 150,000 images.

Authors:  Edward H Snell; Joseph R Luft; Stephen A Potter; Angela M Lauricella; Stacey M Gulde; Michael G Malkowski; Mary Koszelak-Rosenblum; Meriem I Said; Jennifer L Smith; Christina K Veatch; Robert J Collins; Geoff Franks; Max Thayer; Christian Cumbaa; Igor Jurisica; George T Detitta
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2008-10-18

9.  Using textons to rank crystallization droplets by the likely presence of crystals.

Authors:  Jia Tsing Ng; Carien Dekker; Markus Kroemer; Michael Osborne; Frank von Delft
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2014-09-27
  9 in total

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