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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: Jul 8, 2025

Transcriptome Analysis of Single Cells
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Transcriptome Analysis of Single Cells

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在单细胞转录组学中检测节奏基因表达.

Bingxian Xu1,2, Dingbang Ma3,4, Katherine Abruzzi5,6

  • 1Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA.

bioRxiv : the preprint server for biology
|December 18, 2023
PubMed
概括
此摘要是机器生成的。

这项研究对单细胞RNA测序数据的昼夜节律检测方法进行了基准. 一种亚抽样和调回归方法提供了一种有效的策略,用于在单细胞水平上识别昼夜基因.

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

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相关实验视频

Last Updated: Jul 8, 2025

Transcriptome Analysis of Single Cells
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Transcriptome Analysis of Single Cells

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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科学领域:

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

背景情况:

  • 昼夜节律是细胞转录-翻译反循环所驱动的基本生物过程.
  • 识别昼夜控制基因对于理解多细胞生物体中的生理协调至关重要.
  • 单细胞RNA测序 (scRNA-seq) 为研究细胞钟提供了强大的工具,但适应现有的检测算法仍然是一个挑战.

研究的目的:

  • 在单细胞RNA测序数据上对现有的昼夜检测算法进行可靠性和效率的基准测试.
  • 为单细胞应用提供适应大量转录基因生物节律检测方法的指导.
  • 确定在单细胞数据集中改进节律检测的机会.

主要方法:

  • 在scRNA-seq数据上对常用的昼夜检测算法进行基准测试.
  • 在可靠性和效率方面评估算法性能.
  • 建议并测试与回归相结合的部分采样程序.

主要成果:

  • 评估各种算法在scRNA-seq数据中检测昼夜节律的适用性.
  • 在将批量方法应用于单细胞数据时,确定特定的挑战和局限性.
  • 证明采用和回归的部分采样程序是单细胞昼夜基因检测的有效策略.

结论:

  • 现有的昼夜检测方法需要适应,以便有效地使用单细胞RNA测序数据.
  • 拟议的部分采样和和回归策略提高了单细胞研究中昼夜基因识别的效率和稳定性.
  • 这项工作为推进单细胞水平的昼夜动态分析提供了一个框架.