Automatic particle selection: results of a comparative study
Automatic particle selection: results of a comparative study
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DOI：
10.1016/j.jsb.2003.09.033
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发表时间：
2004-01-01
影响因子：
3
通讯作者：
Potter, CS
中科院分区：
文献类型：
--
作者：
Zhu, YX;Carragher, B;Potter, CS
当需要十万甚至一百万个粒子的数据集用于近原子分辨率的结构确定时，使用低温电子显微镜（cryoEM）获取的图像中的单个粒子的手动选择将成为显著的瓶颈。因此，全自动粒子选择的算法开发是cryoEM领域的重要研究目标。一些研究小组正在这一领域取得有希望的新进展。使用一组标准的cryoEM图像的算法评估是该算法开发的一个重要方面。考虑到这一目标，粒子选择“烘烤”被纳入cryoEM自动粒子选择多学科研讨会的计划。12个小组通过提交在一个公共数据集上测试他们自己的算法的结果来参与。该数据集由82个散焦对的高倍显微照片组成，含有使用cryoEM获得的匙孔血蓝蛋白颗粒。烘烤结果沿着研讨会讨论摘要。与会者一致认为，建立基准粒子和使用烘烤来评估算法有助于促进完全自动化粒子选择的算法开发，并且应维护和扩展为支持烘烤而建立的基础设施，以包括更大和更多样化的数据集，以及未来评估的更多标准。(C)2003年爱思唯尔公司All rights reserved.
Manual selection of single particles in images acquired using cryo-electron microscopy (cryoEM) will become a significant bottleneck when datasets of a hundred thousand or even a million particles are required for structure determination at near atomic resolution. Algorithm development of fully automated particle selection is thus an important research objective in the cryoEM field. A number of research groups are making promising new advances in this area. Evaluation of algorithms using a standard set of cryoEM images is an essential aspect of this algorithm development. With this goal in mind, a particle selection "bakeoff" was included in the program of the Multidisciplinary Workshop on Automatic Particle Selection for cryoEM. Twelve groups participated by submitting the results of testing their own algorithms on a common dataset. The dataset consisted of 82 defocus pairs of high-magnification micrographs, containing keyhole limpet hemocyanin particles, acquired using cryoEM. The results of the bakeoff are presented in this paper along with a summary of the discussion from the workshop. It was agreed that establishing benchmark particles and using bakeoffs to evaluate algorithms are useful in promoting algorithm development for fully automated particle selection, and that the infrastructure set up to support the bakeoff should be maintained and extended to include larger and more varied datasets, and more criteria for future evaluations. (C) 2003 Elsevier Inc. All rights reserved.