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

Benchmarking AI scientists for omics data-driven biological discovery.

Bioinformatics (Oxford, England)·2026
Same author

A multi-modal diffusion model with dual-cross-attention for multi-omics data generation and translation.

Nature communications·2026
Same author

A generic reference defined by consensus peaks for single-cell ATAC-seq data analysis.

Nature communications·2026
Same author

hECA v2.0: an AI-ready ensemble cell atlas of single-cell RNA and ATAC sequencing data.

Scientific data·2025
Same author

ERNIE-RNA: an RNA language model with structure-enhanced representations.

Nature communications·2025
Same author

Computational methods and data resources for predicting tumor neoantigens.

Briefings in bioinformatics·2025

相关实验视频

Updated: Jul 12, 2025

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

792

隐藏特征提取与基于先前的自我注意框架用于空间转录学.

Zhen Li1, Xiaoyang Chen1, Xuegong Zhang1

  • 1Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China.

Genome research
|October 30, 2023
PubMed
概括
此摘要是机器生成的。

空间转录学 (ST) 的新框架PAST通过整合先前信息和自我注意机制,有效地表征空间领域. 这种方法增强了下游分析,并使新的应用,如使用参考数据进行自动注释,成为可能.

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

4.9K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

相关实验视频

Last Updated: Jul 12, 2025

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

792
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
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

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) 正在迅速发展,需要强大的方法来描述空间域的特征.
  • 准确的空间域识别对于下游的ST数据分析和生物解释至关重要.

研究的目的:

  • 为空间转录学 (PAST) 引入一种新的基于先前的自我注意框架.
  • 加强空间领域的表征,并促进ST数据的下游分析.

主要方法:

  • PAST使用一个变量图卷积自编码器.
  • 它通过贝叶斯神经网络集成先前信息,并使用自我注意力机制捕捉空间模式.
  • 一个波动步行采样器策略确保了可扩展的应用.

主要成果:

  • PAST有效地描述了跨多种ST数据集的空间域.
  • 该框架有助于ST可视化,空间轨迹推断和伪时分析.
  • PAST在多切片联合嵌入和空间域的自动注释方面展示了优势.

结论:

  • PAST是第一个将参考数据集成为ST数据分析的ST方法.
  • 这种方法通过实现定制的参考数据集成来扩大ST技术的适用性.
  • PAST为破译复杂的空间转录基因数据开辟了新的途径.