低温电子层析成像
生物
多细胞生物
工作流程
细胞骨架
计算生物学
低温电子显微
电子断层摄影术
细胞生物学
计算机科学
断层摄影术
人工智能
纳米技术
生物物理学
细胞
生物化学
材料科学
物理
扫描透射电子显微镜
光学
数据库
透射电子显微镜
作者
Jonathan Schneider,Marion Jasnin
标识
DOI:10.1016/j.ceb.2024.102356
摘要
Cryo-electron tomography (cryo-ET) has begun to provide intricate views of cellular architecture at unprecedented resolutions. Considerable efforts are being made to further optimize and automate the cryo-ET workflow, from sample preparation to data acquisition and analysis, to enable visual proteomics inside of cells. Here, we will discuss the latest advances in cryo-ET that go hand in hand with their application to the actin cytoskeleton. The development of deep learning tools for automated annotation of tomographic reconstructions and the serial lift-out sample preparation procedure will soon make it possible to perform high-resolution structural biology in a whole new range of samples, from multicellular organisms to organoids and tissues.
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