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

RNA-seq03:21

RNA-seq

9.9K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.9K

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

Personalized targeting of BCL2 family proteins overcomes acquired resistance to BRAF-MEK inhibitors in preclinical melanoma.

Nature communications·2026
Same author

FGFR1 but not S6K1/2 drives intrinsic BRAF inhibitor resistance in melanoma.

Cell death discovery·2026
Same author

A Spatial Atlas of Muscle-Invasive Bladder Cancer Reveals Lineage-Specific Vulnerabilities and Immune Architecture.

Cancer discovery·2026
Same author

Global patterns of mutational profiles in biliary tract cancer.

Journal of hepatology·2026
Same author

FOXM1-Specific TCR-Engineered T Cells Target Non-Small Cell Lung Cancer.

Cancer immunology research·2026
Same author

Mucosal Versus Submucosal Lymphovascular Invasion in Early Esophageal Cancer.

Annals of surgical oncology·2026

相关实验视频

Updated: Jun 25, 2025

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
08:30

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

12.9K

一个黄金标准衍生模块化条形码方法来癌症转录组学.

Yan Zhu1, Mohamad Karim I Koleilat1, Jason Roszik2

  • 1Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

Cancers
|May 25, 2024
PubMed
概括

研究人员从癌症基因组图谱 (TCGA) 开发了灵活的基因表达模块,以简化癌症转录组分析. 这种方法有助于发现基因关系,改进数据分析和解码复杂的癌症数据,用于研究和潜在的临床应用.

关键词:
条形码编码 条形码编码癌症 癌症 癌症 癌症 癌症这些模块是模块模块.这是下一代测序.

更多相关视频

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples
08:18

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Published on: April 7, 2023

1.6K
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

相关实验视频

Last Updated: Jun 25, 2025

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
08:30

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

12.9K
Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples
08:18

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Published on: April 7, 2023

1.6K
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

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.
  • 癌症研究 癌症研究

背景情况:

  • 研究癌症转录组在管理大型数据集方面存在挑战.
  • 现有的方法需要重要的生物信息学专业知识.

研究的目的:

  • 开发一种用户友好的方法来分析癌症转录基因组数据.
  • 为特定的癌症类型创建可适应的基因表达模块 (条形码).
  • 为了促进研究人员的假设生成和测试.

主要方法:

  • 从癌症基因组图谱 (TCGA) 数据中组装癌症类型特定的基因表达模块.
  • 利用基因模块作为数据分析的灵活条形码.
  • 开发模块创建和解释的工具.

主要成果:

  • 模块准确地捕获与特定癌症类型相关的功能相关基因.
  • 证明了发现新型基因关系和功能性成员资格的能力.
  • 展示了各种数据集的改进和加速分析,包括单细胞RNA测序.
  • 验证了重建和扩展已知的癌症亚型划分方案的能力.
  • 能够跨越不同的基因特征,并应用单细胞数据.

结论:

  • 拟议的模块化条形码方法提供了一种灵活和用户友好的方法来解码全转录组数据.
  • 这一战略提高了非生物信息学家的数据分析可访问性.
  • 这种方法在癌症研究中具有研究和临床应用的潜力.