Holleman Ethan T, Duguid Erica, Keefe Lisa J, Bowman Sarah E J
Hauptman-Woodward Medical Research Institute, 700 Ellicott Street, Buffalo, NY 14203, USA.
Industrial Macromolecular Crystallography Association Collaborative Access Team, Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA.
J Appl Crystallogr. 2021 Feb 19;54(Pt 2):673-679. doi: 10.1107/S1600576721000108. eCollection 2021 Apr 1.
is a Python-based graphical user interface designed to streamline viewing and analysis of images to monitor crystal growth, with a specific target to enable users of the High-Throughput Crystallization Screening Center at Hauptman-Woodward Medical Research Institute (HWI) to efficiently inspect their crystallization experiments. aims to increase efficiency, reducing time spent manually reviewing crystallization images, and to improve the potential of identifying positive crystallization conditions. provides a streamlined one-click graphical interface for the Machine Recognition of Crystallization Outcomes (MARCO) convolutional neural network for automated image classification, as well as powerful tools to view and score crystallization images, to compare crystallization conditions, and to facilitate collaborative review of crystallization screening results. Crystallization images need not have been captured at HWI to utilize 's basic functionality. is free to use and modify for both academic and commercial use under the terms of the copyleft GNU General Public License v3.0.
是一个基于Python的图形用户界面,旨在简化图像的查看和分析以监测晶体生长,其特定目标是使豪普特曼-伍德沃德医学研究所(HWI)高通量结晶筛选中心的用户能够有效地检查他们的结晶实验。旨在提高效率,减少手动查看结晶图像所花费的时间,并提高识别阳性结晶条件的可能性。为用于自动图像分类的结晶结果机器识别(MARCO)卷积神经网络提供了一个简化的一键式图形界面,以及用于查看和评分结晶图像、比较结晶条件以及促进结晶筛选结果协作审查的强大工具。无需在HWI采集结晶图像即可使用的基本功能。根据左版GNU通用公共许可证v3.0的条款,可免费用于学术和商业用途并进行修改。