Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A predicted model-aided one-step classification-multireconstruction algorithm for X-ray free-electron laser single-particle imaging.

IUCrJ·2024
Same author

Structural basis for the interaction between human coronavirus HKU1 spike receptor binding domain and its receptor TMPRSS2.

Cell discovery·2024
Same author

A modified phase-retrieval algorithm to facilitate automatic de novo macromolecular structure determination in single-wavelength anomalous diffraction.

IUCrJ·2024
Same author

The EV71 2A protease occupies the central cleft of SETD3 and disrupts SETD3-actin interaction.

Nature communications·2024
Same author

Solving protein structures by combining structure prediction, molecular replacement and direct-methods-aided model completion.

IUCrJ·2024
Same author

Nucleic-acid-triggered NADase activation of a short prokaryotic Argonaute.

Nature·2023

相关实验视频

Updated: Jun 23, 2025

Single Particle Electron Microscopy Reconstruction of the Exosome Complex Using the Random Conical Tilt Method
12:10

Single Particle Electron Microscopy Reconstruction of the Exosome Complex Using the Random Conical Tilt Method

Published on: March 28, 2011

23.5K

一个预测的模型辅助重建算法,用于X射线自由电子激光单粒子成像.

Zhichao Jiao1, Yao He2, Xingke Fu1

  • 1Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190, People's Republic of China.

IUCrJ
|June 21, 2024
PubMed
概括

我们开发了一个新的算法来改进X射线自由电子激光 (XFEL) 数据重建. 这种方法提高了从衍射模式确定蛋白质分子结构的准确性和效率.

关键词:
3D重建重建的3D重建在X射线自由电子激光器.在XFELs中使用XFEL.分子定向的确定分子定向的确定阶段问题问题阶段问题蛋白质结构 蛋白质结构单个粒子的单个粒子.一个粒子成像技术

更多相关视频

Single Particle Cryo-Electron Microscopy: From Sample to Structure
11:52

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

8.5K
A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion
13:43

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

13.1K

相关实验视频

Last Updated: Jun 23, 2025

Single Particle Electron Microscopy Reconstruction of the Exosome Complex Using the Random Conical Tilt Method
12:10

Single Particle Electron Microscopy Reconstruction of the Exosome Complex Using the Random Conical Tilt Method

Published on: March 28, 2011

23.5K
Single Particle Cryo-Electron Microscopy: From Sample to Structure
11:52

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

8.5K
A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion
13:43

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

13.1K

科学领域:

  • 结构生物学是结构生物学.
  • 生物物理学的生物物理.
  • 在X射线晶体学.

背景情况:

  • 超强,超快的X射线自由电子激光器 (XFEL) 允许单个蛋白质分子的成像.
  • 从XFEL数据准确地重建结构是具有挑战性的.
  • 关键的挑战包括确定衍射模式的方向和检索相位信息.

研究的目的:

  • 在XFEL数据中引入一种用于方向确定和相检索的新型算法.
  • 为了提高XFEL数据重建的成功率,准确性和效率.
  • 为了使单个蛋白质分子的结构分析更加精确.

主要方法:

  • 开发一个预测模型辅助算法.
  • 在各种模拟的XFEL数据集上测试算法.
  • 专注于方向确定和阶段检索技术.

主要成果:

  • 数据重建成功率的显著改善.
  • 提高了确定分子方向的准确性.
  • 提高处理XFEL衍射数据的效率.
  • 成功的阶段检索用于结构恢复.

结论:

  • 预测的模型辅助算法对于XFEL数据重建是有效的.
  • 该方法解决了导向和阶段确定方面的关键挑战.
  • 这一进步有助于使用XFELs更强大,更有效地确定蛋白质结构.