APPLE picker: Automatic particle picking, a low-effort cryo-EM framework.
APPLE picker: Automatic particle picking, a low-effort cryo-EM framework.
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DOI：
10.1016/j.jsb.2018.08.012
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发表时间：
2018-11
影响因子：
3
通讯作者：
Singer A
中科院分区：
文献类型：
--
作者：
Heimowitz A;Andén J;Singer A
粒子拾取是单粒子冷冻电子显微镜（Cryo-EM）的计算管道中的关键第一步。在粒子上，手动选择许多粒子通常是耗时的，而基于模板的粒子拾取是一种流行的方法，它可能会在选择过程中引入手动偏见。本文介绍了Apple（以低使用用户的努力挑选），这是一种简单的新方法，用于快速，准确且无模板的粒子拾取。蛋白酶体，70s核糖体和钥匙孔血胶蛋白项目。
Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. While template-based particle picking is currently a popular approach, it may suffer from introducing manual bias into the selection process. In addition, this approach is still somewhat time-consuming. This paper presents the APPLE (Automatic Particle Picking with Low user Effort) picker, a simple and novel approach for fast, accurate, and template-free particle picking. This approach is evaluated on publicly available datasets containing micrographs of β-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.
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影响因子：
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作者：
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Stark, Holger
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作者：
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通讯作者：
FONGLOCHOVSKY, A
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作者：
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