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相关概念视频

Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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相关实验视频

Updated: May 29, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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用STALocator进行单细胞转录组学的空间转录组学辅助定位.

Shang Li1, Qunlun Shen1, Shihua Zhang2

  • 1NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China; School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.

Cell systems
|February 4, 2025
PubMed
概括
此摘要是机器生成的。

STALocator将单个细胞映射到空间转录组数据,改进空间组织重建和基因表达分析,以获得更好的生物洞察力.

关键词:
数据整合数据集成.一个单细胞RNA测序.空间定位的空间定位空间转录学 空间转录学监督的自动编码器.

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Method for Labeling Transcripts in Individual Escherichia coli Cells for Single-molecule Fluorescence In Situ Hybridization Experiments
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Use of Single Molecule Fluorescent In Situ Hybridization SM-FISH to Quantify and Localize mRNAs in Murine Oocytes
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科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 提供了高分辨率的基因表达,但缺乏空间上下文.
  • 空间转录学 (ST) 提供空间信息,但与scRNA-seq.q.相比,数据质量较差.
  • 整合这些技术对于理解细胞组织和功能至关重要.

研究的目的:

  • 开发STALocator,一种用于准确地定位空间转录组学数据中的单个细胞的新方法.
  • 加强对空间基因表达模式的分析,重建细胞组织.
  • 改进从各种空间数据类型中预测全基因组基因表达的方法.

主要方法:

  • 开发STALocator算法用于细胞到ST数据定位.
  • 使用模拟数据集进行应用和验证.
  • 对人类大脑和状细胞癌数据集的测试 (例如,Slide-seqV2,FISH,Xenium).

主要成果:

  • 在模拟数据上,STALocator与现有的本地化方法相比,表现优越.
  • 成功重建了人类大脑和癌症组织中关键细胞群体的空间组织.
  • 增强基因表达模式和预测FISH和Xenium数据的全基因组表达.
  • 确定了更多的空间变量基因和生物学相关的基因本体学 (GO) 术语.

结论:

  • STALocator有效地整合了scRNA-seq和ST数据,克服了数据质量的限制.
  • 该方法能够对细胞空间结构进行强大的重建,并增强基因表达分析.
  • 通过识别新的空间模式和关系,STALocator促进了更深层次的生物发现.