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首页> 外文期刊>Acta crystallographica. Section D, Biological crystallography. >Establishing a training set through the visual analysis of crystallization trials. Part I: ～150 000 images
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Establishing a training set through the visual analysis of crystallization trials. Part I: ～150 000 images

机译：建立一个通过视觉训练集结晶试验分析。000张图片

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摘要

Structural crystallography aims to provide a three-dimensional representation of macromolecules. Many parts of the multistep process to produce the three-dimensional structural model have been automated, especially through various structural genomics projects. A key step is the production of crystals for diffraction. The target macromolecule is combined with a large and chemically diverse set of cocktails with some leading ideally, but infrequently, to crystallization. A variety of outcomes will be observed during these screening experiments that typically require human interpretation for classification. Human interpretation is neither scalable nor objective, highlighting the need to develop an automatic computer-based image classification. As a first step towards automated image classification, 147 456 images representing crystallization experiments from 96 different macromolecular samples were manually classified. Each image was classified by three experts into seven predefined categories or their combinations. The resulting data where all three observers are in agreement provides one component of a truth set for the development and rigorous testing of automated image-classification systems and provides information about the chemical cocktails used for crystallization. In this paper, the details of this study are presented.
机译：结构晶体学的目标是提供一个的三维表示大分子。生产三维过程结构模型已经自动化,特别是通过各种结构基因组学项目。关键的一步是晶体的生产衍射。一个大型和化学多样化的鸡尾酒和一些重要的理想,但是很少,结晶。结果将被观察到在这些筛选实验,通常需要人工解释的分类。解释是可伸缩的和目标,强调了需要开发一个自动基于计算机的图像分类。一步自动图像分类,147年456张图片代表结晶实验从96种不同的大分子样品是手工分类。由三个专家分类为七个预定义的类别或它们的组合。数据,所有三个观察家一致提供了一套真理的一个组件开发和严格的测试自动化图像分类系统,并提供信息使用的化学混合物结晶。提出了本研究。

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