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

Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

8.8K
The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
8.8K
Overview of Cell Signaling01:23

Overview of Cell Signaling

24.1K
Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
Cells respond to many types of information, often through receptor proteins positioned on the membrane. For example, skin cells respond to and transmit touch...
24.1K
What is Cell Signaling?02:03

What is Cell Signaling?

129.6K
Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate to respond to the environment.
129.6K

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

sMIE: revealing critical transitions in complex biological systems using single-sample mutual information entropy.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

Self-supervised reservoir computing with spatial-temporal encoding for identifying critical transitions.

Nature communications·2026
Same author

sPGGM: a sample-perturbed Gaussian graphical model for identifying pre-disease stages and signaling molecules of disease progression.

National science review·2025
Same author

A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data.

National science review·2025
Same author

One-core neuron deep learning for time series prediction.

National science review·2025
Same author

eMCI: An Explainable Multimodal Correlation Integration Model for Unveiling Spatial Transcriptomics and Intercellular Signaling.

Research (Washington, D.C.)·2024

相关实验视频

Updated: Jan 13, 2026

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis
07:58

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis

Published on: March 9, 2022

1.9K

Hi-C3:一种基于统计推断的模型,用于重建高阶细胞-细胞通信网络.

Yuyan Tong1, Renhao Hong1, Meng Li2

  • 1School of Mathematics, South China University of Technology, No. 381 Wushan Road, Tianhe District, Guangzhou 510640, Guangdong, China.

Briefings in bioinformatics
|October 29, 2025
PubMed
概括

多细胞生物依赖细胞-细胞通信 (CCC) 进行协调功能. 一个新的框架,Hi-C3,从单细胞RNA测序数据中推断出双向和高阶CCC模式,揭示出复杂的通信网络.

关键词:
高阶细胞细胞通信.细胞间通信是细胞间的通信.最大的概率估计估计.简化的复杂的复杂.一个单细胞RNA-seqq.

更多相关视频

Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing
08:58

Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing

Published on: August 1, 2025

2.8K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

4.0K

相关实验视频

Last Updated: Jan 13, 2026

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis
07:58

Computational Reconstruction of Pancreatic Islets as a Tool for Structural and Functional Analysis

Published on: March 9, 2022

1.9K
Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing
08:58

Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing

Published on: August 1, 2025

2.8K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

4.0K

科学领域:

  • 计算生物学 计算生物学
  • 系统生物学 系统生物学
  • 基因组学就是基因组学.

背景情况:

  • 多细胞生物需要协调的细胞-细胞通信 (CCC) 来进行发育和功能.
  • 目前使用单细胞RNA测序 (scRNA-seq) 的方法主要推断为对的联体受体相互作用 (LRIs).
  • 生物过程通常涉及多种细胞类型的协调行动,需要超越对对相互作用的模型.

研究的目的:

  • 开发一个统计框架,Hi-C3,用于从scRNA-seq数据中推断双向和高阶CCC模式.
  • 模拟受体表达受多种联结体产生细胞类型的集体信号的影响.
  • 在复杂的多细胞网络中确定关键的蜂通信枢纽.

主要方法:

  • 开发了Hi-C3,一个使用网络扩散和流行病动态原则的统计推理框架.
  • 模拟受体表达作为由集体信号调节的Poisson分布变量.
  • 采用基于概率的预期最大化 (EM) 算法和修改的PageRank算法进行网络分析.

主要成果:

  • Hi-C3成功地推断出与最先进的方法可比的对联CCC.
  • 该框架独特地揭示了复杂的高级CCC结构.
  • 在Arabidopsis thaliana和结直肠癌数据集中,通过独立的生物和空间证据支持确定了关键的细胞通信枢纽.

结论:

  • Hi-C3提供了一个强大的统计模型和计算框架,用于发现更高阶的CCC.
  • 该方法揭示了复杂的多细胞信号结构,经常被双向推断遗漏.
  • 提供了关于细胞组织和发育和疾病中的通信网络的新见解.