MRC Laboratory of Molecular Biology, Francis Crick Avenue, CB2 0QH Cambridge, UK.
Biochem J. 2021 Dec 22;478(24):4169-4185. doi: 10.1042/BCJ20210708.
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.
我们在 RELION 软件的第四个主要版本中描述了用于电子冷冻显微镜(cryo-EM)图像处理的新工具。特别是,我们引入了 VDAM,一种具有自适应矩估计的变尺度梯度下降算法,用于图像精修;一种用于无监督选择 2D 类的卷积神经网络;以及一个灵活的框架,用于在预定义工作流程中设计和执行多个作业。此外,我们还提供了一个名为 MDCatch 的独立实用程序,它将该框架内作业的执行与显微镜数据采集过程中的元数据收集联系起来。这些新工具旨在提供快速而稳健的无监督 cryo-EM 结构确定程序,具有即时处理和开发灵活、高通量结构确定流水线的潜在应用。我们在 12 个公开可用的 cryo-EM 数据集上说明了它们的潜力。