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

Gastrulation01:56

Gastrulation

54.9K
Gastrulation establishes the three primary tissues of an embryo: the ectoderm, mesoderm, and endoderm. This developmental process relies on a series of intricate cellular movements, which in humans transforms a flat, “bilaminar disc” composed of two cell sheets into a three-tiered structure. In the resulting embryo, the endoderm serves as the bottom layer, and stacked directly above it is the intermediate mesoderm, and then the uppermost ectoderm. Respectively, these tissue strata...
54.9K

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

[Research progress in mechanisms of Tripterygium wilfordii and its active ingredients in treatment of inflammatory bowel disease].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2026
Same author

Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomics.

Nature communications·2026
Same author

Correlation between tumor mutational burden and CT radiographic features in EGFR exon 19 deletion-mutated lung adenocarcinoma: a diagnostic accuracy study.

Frontiers in medicine·2026
Same author

Multiscale learning of gene network-driven phenotypic dynamics of single cells.

Molecular systems biology·2026
Same author

Inferring stochastic dynamics by biophysical Neural ODE using single-cell transcriptomics.

Nature communications·2026
Same author

Robust identification of cell-cell communication heterogeneity in single cells.

bioRxiv : the preprint server for biology·2026

相关实验视频

Updated: May 12, 2025

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
05:45

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

2.0K

通过单细胞和空间转录组学来转移多细胞组织的学习.

Yecheng Tan1,2, Ai Wang3, Zezhou Wang1,4

  • 1Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China.

PLoS computational biology
|April 21, 2025
PubMed
概括

iSORT集成了单细胞RNA测序和空间转录组学数据,以揭示细胞的空间组织. 这种方法可以识别关键的空间组织基因 (SOG),驱动组织模式和血管异常.

更多相关视频

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

6.5K
Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights
08:23

Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights

Published on: June 28, 2024

659

相关实验视频

Last Updated: May 12, 2025

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
05:45

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

2.0K
Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

6.5K
Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights
08:23

Author Spotlight: Integrating Single-Cell Transcriptomics with Organoid Cultures for Advanced Research and Therapeutic Insights

Published on: June 28, 2024

659

科学领域:

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

背景情况:

  • 生物组织表现出复杂的基因表达和多细胞模式,这对于理解发育和疾病至关重要.
  • 单细胞RNA测序 (scRNA-seq) 提供了全面的基因覆盖,但缺乏空间上下文.
  • 空间转录学 (ST) 提供空间信息,但在基因分析方面存在局限性.

研究的目的:

  • 通过集成scRNA-seq和ST数据来开发一种新的计算方法来破译细胞空间组织.
  • 确定驱动观察到的多细胞模式的空间组织基因 (SOG).
  • 推断伪生长轨迹,分析组织发育和疾病机制.

主要方法:

  • 开发了iSORT,一种转移学习方法,利用神经网络将基因表达映射到空间位置.
  • 集成scRNA-seq和ST数据以重建单细胞规模的多细胞组织.
  • 将iSORT应用于各种生物系统,包括人类皮质,小鼠胚胎和动脉样硬化动脉.

主要成果:

  • iSORT准确地重建了各种生物系统的多细胞组织.
  • 确定了对于组织模式至关重要的空间组织基因 (SOG).
  • 证明了动脉样硬化动脉中的SOG与血管结构异常密切相关.
  • 使用SpaRNA速度概念推断伪增长轨迹.

结论:

  • iSORT是一个准确而实用的工具,用于整合scRNA-seq和ST数据以了解空间生物学.
  • 已识别的SOG提供了对基础组织发育和疾病病理学的分子机制的洞察.
  • 这种方法推动了多细胞组织和空间基因组学的研究.