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

Chemotaxis and Direction of Cell Migration01:21

Chemotaxis and Direction of Cell Migration

5.0K
Cells can detect chemical cues in their environment and reorganize the cytoskeleton to migrate toward them or away from them. This directional migration, called chemotaxis, is essential during embryogenesis and development, immune response, tissue repair and regeneration, and reproduction. These chemical cues can either attract or repel the cell's movement. For example, axon development is determined by a combination of chemoattractants and chemorepellents that direct the growing axon...
5.0K

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

Zero-shot reconstruction of mutant spatial transcriptomes.

Patterns (New York, N.Y.)·2026
Same author

Optogenetic LTP Manipulation and Mathematical Modeling to Investigate Value Plasticity of the Instructive Signal in Mice.

Bio-protocol·2026
Same author

Spatially resolved mapping of tau amplification rates via differentiable simulation of prion-like propagation.

bioRxiv : the preprint server for biology·2026
Same author

Independence and coherence in temporal sequence computation across the fronto-parietal network.

Nature communications·2026
Same author

Decomposing heterogeneity in disease progression speeds and pathways.

NPJ digital medicine·2026
Same author

Technical development of two-photon optogenetic stimulation and its potential application to brain-machine interfaces.

Neurophotonics·2026

相关实验视频

Updated: May 5, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

20.2K

一个数据驱动的框架,将连接体与空间基因表达梯度联系起来,灵感来自化学亲和理论.

Jigen Koike1,2, Ken Nakae3,4, Riichiro Hira5

  • 1Laboratory of Data-driven Biology, Graduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima 739-8526, Japan.

Proceedings of the National Academy of Sciences of the United States of America
|March 3, 2026
PubMed
概括

SPERRFY使Sperry开始运行

关键词:
正规相关性分析 (CCA)化学的亲和力理论.连接ome 连接ome 连接ome神经线路的神经线路.转录组 (transcriptome) 是一个转录组.

更多相关视频

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations
11:36

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations

Published on: April 21, 2023

2.7K
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

1.0K

相关实验视频

Last Updated: May 5, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

20.2K
Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations
11:36

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations

Published on: April 21, 2023

2.7K
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

1.0K

科学领域:

  • 神经科学是一个神经科学.
  • 遗传学 遗传学 是一个
  • 计算生物学 计算生物学

背景情况:

  • 了解大脑全神经电路布线的遗传机制至关重要.
  • 斯佩瑞的化学亲和理论通过分子梯度解释了轴突投射,但仅限于感官系统.

研究的目的:

  • 开发一个数据驱动的框架,SPERRFY,用于将Sperry的理论应用于全脑连接.
  • 推断潜在的位置梯度指导轴突线路贯穿整个大脑.

主要方法:

  • 整合了连接原子数据与来自艾伦老鼠大脑图谱的空间转录原子资料.
  • 采用正统相关性分析 (CCA) 来识别关键的位置梯度.
  • 开发基于推断梯度的连接重建模型.

主要成果:

  • SPERRFY成功地推断出底层轴突电线的潜在位置梯度.
  • 连接重建显示了强大的预测性能.
  • 确定了可能参与定位布线的候选基因.

结论:

  • SPERRFY将Sperry的化学亲和理论扩展到整个大脑尺度上.
  • 为理解遗传编码的大脑全局电路提供了一个统一的框架.
  • 提供了对神经发育和连接性的分子见解.