Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain.
Chem Rev. 2022 Sep 14;122(17):13915-13951. doi: 10.1021/acs.chemrev.1c00850. Epub 2022 Jul 4.
Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.
低温电子显微镜(CryoEM)已成为结构生物学中至关重要的技术。它是一个跨学科领域,利用生物化学、物理学和图像处理等其他学科的进展。这三个基本支柱的创新推动了过去十年中 CryoEM 的发展。本文综述了图像处理在当前单颗粒分析(SPA)CryoEM 重建工作流程中的主要贡献。我们的综述强调了算法在工作流程不同步骤中的时间演变,将其分为两组方法:分析方法和深度学习算法。我们对当前的最新技术进行了分析。最后,我们讨论了 SPA 中 CryoEM 图像处理方法发展中仍然需要解决的新出现的问题和挑战。