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相关概念视频

Cryo-electron Microscopy01:28

Cryo-electron Microscopy

3.4K
Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...
3.4K

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相关实验视频

Updated: Jul 16, 2025

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency
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Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

Published on: May 10, 2024

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一个强大的正常化局部波器,可以直接从冷-EM地图中估计组合异质性.

Björn O Forsberg1,2, Pranav N M Shah3, Alister Burt4

  • 1Department of Physiology and Pharmacology, Karolinska Institute, 171 77, Stockholm, Sweden. bjorn.forsberg@ki.se.

Nature communications
|September 19, 2023
PubMed
概括
此摘要是机器生成的。

在冷电子显微镜 (cryo-EM) 重建中估计异质性是具有挑战性的. 本研究引入了一个快速的空间过算法来量化重建异质性和宏分子组件占用.

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Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
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Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

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Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope
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Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Published on: March 16, 2022

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相关实验视频

Last Updated: Jul 16, 2025

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency
06:41

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

Published on: May 10, 2024

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Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
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Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

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Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope
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科学领域:

  • 结构生物学 结构生物学
  • 生物物理学的生物物理.
  • 计算生物学 计算生物学

背景情况:

  • 低温电子显微镜 (cryo-EM) 对于生物分子复合体的3D可视化至关重要.
  • 在冷EM重建中估计异质性仍然是一个重大挑战.
  • 目前的方法侧重于减少异质性,而不是量化它.

研究的目的:

  • 开发一种快速简单的算法,用于估计冷EM重建中的异质性.
  • 用空间过来估计宏分子组件占用率.
  • 提供一种评估和潜在纠正组合异质性的方法.

主要方法:

  • 开发一种新的空间过算法.
  • 算法的应用来估计重建异质性.
  • 分析对比度损失以推断组成异质性.
  • 证明修改重建以模拟更改的组成部分占用率.

主要成果:

  • 开发的算法提供了快速和简单的冷EM重建异质性的估计.
  • 该方法成功地接近了宏分子组件占用率.
  • 构成异质性可以根据对比度损失来估计.
  • 重建可以调整以反映不同组成部分的占用情况.

结论:

  • 这种空间过方法为评估冷EM异质性提供了有价值的工具.
  • 该方法可以改善冷EM地图的解释和量化.
  • 它通过提供异质性的直接测量来补充现有的最大概率分类方法.