Plaisier J R, Koning R I, Koerten H K, van Heel M, Abrahams J P
Gorlaeus Laboratories, Leiden Institute of Chemistry, Leiden University, PO Box 9502, 2300 RA Leiden, The Netherlands.
J Struct Biol. 2004 Jan-Feb;145(1-2):76-83. doi: 10.1016/j.jsb.2003.09.030.
We here present TYSON, a new program for automatic and semi-automatic particle selection from electron micrographs. TYSON employs a three-step strategy of searching, sorting and selecting single particles. In the first step, TYSON finds the positions of potential particles by one of three different methods: local averaging, template matching or local variance. The practical merits and drawbacks of these methods are discussed. In the second step, these potential particles are automatically sorted according to their probability of being true positives. Many criteria are provided for this sort. In the final -interactive- step, whole categories of poorly fitting false positives can be removed with a single mouse-click. We present results obtained using cryo-EM micrographs of both spherical virus particles and asymmetric particles. The procedures are fast and use of TYSON allowed, for example, some 20,000 particles to be selected in a single working day.
我们在此展示TYSON，这是一个用于从电子显微照片中自动和半自动选择粒子的新程序。TYSON采用搜索、分类和选择单个粒子的三步策略。第一步，TYSON通过三种不同方法之一找到潜在粒子的位置：局部平均、模板匹配或局部方差。讨论了这些方法的实际优缺点。第二步，根据这些潜在粒子为真阳性的概率自动对其进行分类。为此分类提供了许多标准。在最后一步（交互式）中，只需单击鼠标即可去除拟合不佳的整类误报。我们展示了使用球形病毒颗粒和不对称颗粒的冷冻电镜显微照片获得的结果。这些程序速度很快，例如，使用TYSON在一个工作日内可以选择约20000个粒子。
