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相关概念视频

Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.6K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
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Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

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Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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相关实验视频

Updated: Jan 12, 2026

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination
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High Precision FRET at Single-molecule Level for Biomolecule Structure Determination

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从衍射有限光中区分单分子结合事件.

Yueming Yin1, Nithin Pathoor2, Kamal Kant Sharma2

  • 1Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, Singapore, Singapore.

Nature communications
|November 7, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的AI模型,即时间对环境卷积神经网络 (T2C CNN),用于分析单分子局部化显微镜视频. 它快速准确地使用一种染料对分子结合类型进行分类,改善了高通量成像.

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Conducting Multiple Imaging Modes with One Fluorescence Microscope
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Conducting Multiple Imaging Modes with One Fluorescence Microscope

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Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes
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Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

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相关实验视频

Last Updated: Jan 12, 2026

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination
11:24

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination

Published on: May 13, 2017

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科学领域:

  • 生物物理学的生物物理.
  • 计算生物学 计算生物学
  • 显微镜的使用方法

背景情况:

  • 单分子定位显微镜 (SMLM) 提供了对分子相互作用的高分辨率洞察力.
  • 在SMLM中分类分子结合类型的传统方法是复杂的,耗时的,通常需要多种染料或动力分析.

研究的目的:

  • 利用SMLM视频开发一种用于同步分类分子结合事件的新方法.
  • 为了利用射有限的光信号中的时空信息,用于绑定类型识别.
  • 为了减少分析高通量单分子成像中的分子相互作用所需的复杂性和时间.

主要方法:

  • 开发一个时间到环境的卷积神经网络 (T2C CNN) 架构.
  • 在T2C CNN中整合了长期的空间卷曲,浅层的交叉连接块,以及一个没有聚合的结构.
  • 应用T2C CNN来分析DNA-PAINT实验视频使用一个光染料.

主要成果:

  • 在分类有约束力的事件视频方面,T2C CNN的准确率高达94.76%.
  • 拟议的方法显著超过现有的最先进的视频分类模型15-25个百分点.
  • 结合类型识别的观察时间从分钟缩短到秒.

结论:

  • 通过分析嵌入的时空信息,T2C CNN有效地使用单个染料从SMLM视频中分类分子结合类型.
  • 这种方法可以实现快速,精确和高通量单分子成像,而无需复杂的实验设置.
  • 这些发现为更有效地分析生物系统中的分子相互作用铺平了道路.