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相关概念视频

X-ray Crystallography02:18

X-ray Crystallography

The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal crystal...
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

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...
Determination of Crystal Structures01:29

Determination of Crystal Structures

In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...

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相关实验视频

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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
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深度学习地图细分用于蛋白质X射线晶体结构确定.

Pavol Skubák1

  • 1Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.

Acta crystallographica. Section D, Structural biology
|June 27, 2024
PubMed
概括
此摘要是机器生成的。

卷积神经网络 (CNN) 可以改善蛋白质结构的确定. 这项研究建议使用CNN对电子密度图进行细分,从而增强X射线晶体学当前的方法.

关键词:
计算建模计算建模卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.密度的修改 密度的修改这是一个实验性的分阶段化.宏分子X射线晶体学 宏分子X射线晶体学分子晶体的分子晶体.蛋白质结构 蛋白质结构一个波长的异常衍射.结构的确定 结构的确定

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科学领域:

  • 结构生物学是结构生物学.
  • 在X射线晶体学.
  • 计算生物学是一种计算生物学.

背景情况:

  • 使用X射线衍射来确定蛋白质结构需要准确的电子密度图.
  • 初始阶段化通常会产生需要通过代电子密度修改来改进的地图.
  • 目前用于改善地图的方法可能是劳动密集型和耗时的.

研究的目的:

  • 通过卷积神经网络 (CNN) 引入一种改进电子密度图的新方法.
  • 评估CNN在细分和完善初始实验阶段地图中的有效性.
  • 为了证明深度学习在加速蛋白质结构解决方案中的潜力.

主要方法:

  • 使用U-net架构的CNN的开发和培训.
  • 监督学习方法使用来自蛋白质数据库X射线数据的大量电子密度图的数据集.
  • 训练CNN的应用用于初始实验相位电子密度图的细分.

主要成果:

  • 拟议的CNN模型成功分割了最初的电子密度图.
  • 基于CNN的细分比传统的代密度修改技术有所改善.
  • 经过训练的网络在各种数据集中表现出强的性能.

结论:

  • 卷积神经网络提供了一种强大而有效的方法来提高蛋白质结晶学中的电子密度图质量.
  • 这种深度学习策略可以显著提高蛋白质结构确定的准确性和速度.
  • U-net 架构非常适合在电子密度图精细化中的细分任务.