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

9.8K
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...
9.8K

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 association between obesity and telomere shortening is mediated through total bilirubin.

Cardiovascular diabetology. Endocrinology reports·2026
Same author

NicheTrans: spatial-aware cross-omics translation.

Nature methods·2026
Same author

Zero-Fluoroscopy Cryoballoon Ablation for Paroxysmal Atrial Fibrillation in a Patient With Dextrocardia: A Case Report.

Pacing and clinical electrophysiology : PACE·2026
Same author

Association of Triglyceride-Glucose-Frailty Index with Cardiovascular Disease and All-Cause Mortality Incidence in Individuals with Cardiovascular-Kidney-Metabolic Syndrome Stages 0-3: A Nationwide Prospective Cohort Study.

Journal of clinical medicine·2026
Same author

Corrigendum to <'Circulating exosome-mediated AMPKα-SIRT1 pathway regulates lipid metabolism disorders in calf hepatocytes'> <[Research in Veterinary Science 169 (2024) /105177]>.

Research in veterinary science·2026
Same author

stGCL: a versatile cross-modality fusion method based on multi-modal graph contrastive learning for spatial transcriptomics.

Genome biology·2026

相关实验视频

Updated: Jun 11, 2025

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

4.9K

SpaGRA:图形增强方便了空间解析的转录组学域识别.

Xue Sun1, Wei Zhang1, Wenrui Li2

  • 1Center of Intelligent Medicine, School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, China.

Journal of genetics and genomics = Yi chuan xue bao
|October 3, 2024
PubMed
概括
此摘要是机器生成的。

通过构建多关系图,SpaGRA 通过构建多关系图来改善空间解析转录学中的空间域识别. 这种新的图形增强方法提高了各种生物组织分析的准确性.

关键词:
几何对比学习学习几何对比图形增强的图形增强方法多头图表注意力网络的注意力网络空间域识别 空间域识别空间分辨的转录学.

更多相关视频

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

653
Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis
07:40

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

110

相关实验视频

Last Updated: Jun 11, 2025

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

4.9K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

653
Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis
07:40

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

110

科学领域:

  • 计算生物学 计算生物学
  • 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:

  • 空间解析的转录学 (SRT) 能够进行组织空间结构的表征.
  • 基于图形的几何深度学习被广泛用于空间域识别.
  • 目前仅依赖空间距离的方法忽视了关键的基因表达相似性,限制了准确性.

研究的目的:

  • 引入SpaGRA,一种用于在SRT数据中自动构建多关系图的新方法.
  • 通过结合各种生物相互作用来提高空间域识别的准确性.
  • 为解决空间转录学的几何对比学习中的采样偏差.

主要方法:

  • SpaGRA利用空间距离作为先前知识,并使用多头图注意力网络 (GAT) 动态调整边缘重量.
  • 它构建多种节点关系,并增强在几何对比学习中传递信息.
  • 多视图关系用于生成负样本,减轻随机选择偏差.

主要成果:

  • 在不同协议的多个数据集中,SpaGRA展示了优越的空间域识别性能.
  • 对小鼠下丘脑的分析揭示了不同的功能区域.
  • 在小鼠胚胎心脏发育中的关键基因的识别和Visium HD数据中癌症相关纤维细胞的可视化.

结论:

  • SpaGRA有效地描述了各种SRT数据集中的空间结构.
  • 该方法增强了对组织结构和生物相互作用的理解.
  • 在转录学研究中,SpaGRA提供了一个强大的空间域识别方法.