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相关概念视频

Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Ribosome Profiling02:24

Ribosome Profiling

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 helps...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

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相关实验视频

Updated: Jul 19, 2026

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

ENGEP:推进空间转录学与准确的未测量基因表达预测.

Shi-Tong Yang1,2, Xiao-Fei Zhang3,4

  • 1School of Mathematics and Statistics, Central China Normal University, Wuhan, China.

Genome biology
|December 22, 2023
PubMed
概括

我们开发了ENGEP,这是一种新的工具,可以预测空间转录组学中缺失的基因表达. 这种方法使用集体学习来增强空间转录学数据,揭示更多的生物学见解.

关键词:
基因表达预测 基因表达预测空间转录组学 空间转录组学这就是 scRNA-seqq.

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A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

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Spatially Resolved, Integrated Single-Cell Multiomic Profiling of the Transcriptome and Epigenomic Targets in Frozen Tissue Sections
09:06

Spatially Resolved, Integrated Single-Cell Multiomic Profiling of the Transcriptome and Epigenomic Targets in Frozen Tissue Sections

Published on: June 12, 2026

相关实验视频

Last Updated: Jul 19, 2026

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
06:02

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

Spatially Resolved, Integrated Single-Cell Multiomic Profiling of the Transcriptome and Epigenomic Targets in Frozen Tissue Sections
09:06

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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:

  • 基于成像的空间转录学为基因表达和空间信息提供单细胞分辨率.
  • 目前的空间转录组学方法对有限数量的基因进行了分析,大多数转录组没有被测量.

研究的目的:

  • 开发一种用于预测空间转录组学数据中未测量的基因表达的计算工具.
  • 为了利用多个单细胞RNA测序数据集作为归算的参考.

主要方法:

  • 开发了ENGEP,一个基于集体学习的计算工具.
  • 利用多个单细胞RNA测序数据集作为参考来预测基因表达.
  • 评估了ENGEP与最先进的工具相比的表现.

主要成果:

  • ENGEP准确地预测了空间转录组学数据中的未测量基因表达.
  • 该工具通过赋予缺失的基因信息,提供了宝贵的生物学见解.
  • 与现有方法相比,ENGEP表现出优越的性能.
  • 在运行时间和内存使用方面表现出卓越的效率,使大数据集具有可扩展性.

结论:

  • ENGEP有效地克服了空间转录组学中低基因检测的局限性.
  • 该工具增强了可以从空间转录组学数据中获得的生物学见解.
  • ENGEP是一个可扩展和高效的解决方案,用于分析大规模的空间转录学数据集.