Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Ribosome Profiling02:24

Ribosome Profiling

3.5K
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...
3.5K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Targeting endoplasmic reticulum export disrupts metabolic resilience in multiple myeloma.

Signal transduction and targeted therapy·2026
Same author

Trastuzumab Deruxtecan Induces Complete Pathological Response in Oligometastatic HER2-Mutant NSCLC: Case Report.

JTO clinical and research reports·2026
Same author

Impact of Disease Biology and Bridging Strategy on Outcomes After CAR-T Cell Therapy in Relapsed/Refractory Multiple Myeloma.

Transplantation and cellular therapy·2026
Same author

The HLH-Risk-Calculator is a machine learning-based tool to predict course & mortality of secondary hemophagocytic lymphohistiocytosis.

Intensive care medicine·2026
Same author

Primary Myelofibrosis (PMF)-The German ONKOPEDIA Guideline 2025.

International journal of cancer·2026
Same author

The German ONKOPEDIA Guideline for Myelofibrosis in 2025-Recommendations of an MPN Expert Panel of the German Society for Hematology and Oncology (DGHO).

International journal of cancer·2026

相关实验视频

Updated: Jun 12, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

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

Published on: October 25, 2018

6.6K

使用BD Rhapsody单细胞分析对复杂人体组织中低mRNA含量细胞进行分析.

Alexandra Scheiber1, Manuel Trebo2, Annabella Pittl1

  • 1Department of Internal Medicine V, Hematology and Oncology and Comprehensive Cancer Center Innsbruck (CCCI), Medical University of Innsbruck, 6020 Innsbruck, Austria.

STAR protocols
|December 11, 2024
PubMed
概括

这项研究提出了一种使用单细胞RNA测序 (scRNA-seq) 有效地恢复具有低mRNA含量的免疫细胞的协议. 该方法优化了组织解离,并利用BD Rhapsody平台来改进细胞捕获和分析.

关键词:
生物信息学是一种生物信息学.癌症 癌症 癌症 癌症在RNAseqqq中使用.测序测序是指测序的时间.

更多相关视频

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.5K
Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

29.8K

相关实验视频

Last Updated: Jun 12, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

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

Published on: October 25, 2018

6.6K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.5K
Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

29.8K

科学领域:

  • 免疫学 免疫学 免疫学
  • 基因组学就是基因组学.
  • 生物技术是生物技术.

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 对于免疫细胞分析至关重要.
  • 低mRNA含量免疫细胞的有效恢复是一个主要的技术挑战.
  • 优化组织解离和scRNA-seq技术对于成功至关重要.

研究的目的:

  • 开发和介绍一个强大的协议,以提高低mRNA含量免疫细胞的恢复.
  • 为了验证协议使用各种组织类型,包括前列腺,肺和肝脏.
  • 通过改进的scRNA-seq.让我们更深入地了解免疫细胞群体.

主要方法:

  • 针对前列腺,肺和肝脏组织的优化组织解离技术.
  • 使用了BD Rhapsody单细胞RNA测序平台.
  • 包含样本标签抗体标签,基于微波的细胞捕获,cDNA合成,库编制和数据预处理.

主要成果:

  • 证明了免疫细胞的有效恢复,包括含有低mRNA含量的免疫细胞.
  • 该协议适用于多种具有挑战性的组织类型.
  • 提供了一个全面的工作流程,从组织解离到数据分析.

结论:

  • 开发的协议显著改善了scRNA-seq.q.的低mRNA含量免疫细胞的恢复.
  • 这种方法提高了研究多样化的免疫细胞种群的能力.
  • 该协议为免疫学和相关领域的研究人员提供了宝贵的资源.