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

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

The purine-rich element-binding protein ChPur-α negatively regulates Hsc70 transcription in Crassostrea hongkongensis.

Cell stress & chaperones·2017
Same author

Improved antitumor effect of ionizing radiation in combination with rapamycin for treating nasopharyngeal carcinoma.

Oncology letters·2017
Same author

Roles of Cells from the Arterial Vessel Wall in Atherosclerosis.

Mediators of inflammation·2017
Same author

Metabolic and microbial signatures in rat hepatocellular carcinoma treated with caffeic acid and chlorogenic acid.

Scientific reports·2017
Same author

Arsenic removal in aqueous solution by a novel Fe-Mn modified biochar composite: Characterization and mechanism.

Ecotoxicology and environmental safety·2017
Same author

Antidiabetic activities of polysaccharides separated from Inonotus obliquus via the modulation of oxidative stress in mice with streptozotocin-induced diabetes.

PloS one·2017

相关实验视频

Updated: Jan 11, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

630

STAHD:一种可扩展和准确的方法,用于检测高分辨率空间转录数据中的空间域.

Zhihua Du1, Di Wang1,2, Qiyi Chen1

  • 1College of Computer Science and Software Engineering, ShenZhen University, Shenzhen, Guangdong, 518000, China.

Bioinformatics (Oxford, England)
|November 10, 2025
PubMed
概括

STAHD是一个新的空间域检测在空间转录组学数据的框架. 它有效地分析大型数据集,提高识别组织异质性和瘤微环境的准确性.

更多相关视频

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.3K
Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
09:32

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

4.3K

相关实验视频

Last Updated: Jan 11, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

630
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.3K
Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
09:32

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

4.3K

科学领域:

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

背景情况:

  • 空间转录学 (ST) 允许研究组织异质性.
  • 当前的ST方法面临着大规模,高分辨率数据的挑战,影响效率和准确性.
  • 需要一个可扩展和精确的空间域检测解决方案.

研究的目的:

  • 在ST数据中开发一个可扩展和有效的空间域检测框架.
  • 提高分析ST数据集的计算效率和集群准确性.
  • 准确地识别组织内空间上不同的区域.

主要方法:

  • 开发了STAHD,一个框架,将图形注意力自编码器与多级k-way图形分区结合起来.
  • 为了高效处理,STAHD将大图分解为紧的子图.
  • 产生低维嵌入来增强分析.

主要成果:

  • 与人类和老鼠数据集的现有方法相比,STAHD显示出更高的性能.
  • 该框架实现了更好的计算效率和集群精度.
  • STAHD准确地识别出空间上不同的瘤微环境和功能区域.

结论:

  • 在ST数据中,STAHD为空间域检测提供了一个可扩展和高效的解决方案.
  • 该方法提高了识别组织异质性的准确性.
  • STAHD提供了对瘤微环境和组织功能有价值的见解.