New tools for automated cryo-EM single-particle analysis in RELION-4.0.
New tools for automated cryo-EM single-particle analysis in RELION-4.0.
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DOI：
10.1042/bcj20210708
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发表时间：
2021-12-22
期刊：
影响因子：
--
通讯作者：
Scheres SHW
中科院分区：
文献类型：
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作者：
Kimanius D;Dong L;Sharov G;Nakane T;Scheres SHW
我们描述了新的电子冷冻显微镜（cryo-EM）的图像处理工具，在第四个主要版本的RELION软件。特别是，我们引入了VDAM，一种具有自适应矩估计的可变度量梯度下降算法，用于图像细化;用于2D类的无监督选择的卷积神经网络;以及用于在预定义工作流中设计和执行多个作业的灵活框架。此外，我们提出了一个独立的实用程序，称为MDCatch，链接在显微镜数据采集过程中的元数据收集在这个框架内的作业的执行。这些新工具旨在为无监督冷冻EM结构确定提供快速和强大的程序，并具有在线处理和开发灵活，高通量结构确定管道的潜在应用。我们说明了他们的潜力12个公开的低温EM数据集。
We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a variable-metric gradient descent algorithm with adaptive moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on 12 publicly available cryo-EM data sets.