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

Protein Networks02:26

Protein Networks

4.0K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.0K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K
Proteomics01:33

Proteomics

7.4K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.4K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

3.8K
3.8K

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

Latent transition analysis of non-suicidal self-injury comorbidity patterns among adolescents: predictive roles of impulsivity, emotional dysregulation, and core self-evaluations.

International journal of clinical and health psychology : IJCHP·2026
Same author

Maternal nonylphenol exposure induces offspring intestinal injury and enteric neuronal defects involving proinflammatory macrophage polarization.

Scientific reports·2026
Same author

Drug-induced hyperuricemia: multi-pathway regulation, causative drugs, and individualized management strategies.

Frontiers in pharmacology·2026
Same author

Interfacial Synergistic Stabilization of CO<sub>2</sub> Foams by Surface-Modified SiO<sub>2</sub> Nanoparticles and Surfactants.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Recent Advances in Cereal Arabinoxylans: A Review of Extraction, Processing and Structure Relationships with Advanced Applications.

Foods (Basel, Switzerland)·2026
Same author

A sustained NAD<sup>+</sup> supplementation-biosynthesis nanoplatform for metabolic restoration in aged bone regeneration.

Bioactive materials·2026
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
查看所有相关文章

相关实验视频

Updated: Jul 16, 2025

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
00:07

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

8.4K

ActivePPI:用马尔科夫随机场量化蛋白质与蛋白质相互作用网络活动.

Chuanyuan Wang1, Shiyu Xu1, Duanchen Sun2

  • 1Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, China.

Bioinformatics (Oxford, England)
|September 12, 2023
PubMed
概括
此摘要是机器生成的。

ActivePPI通过测量网络结构和蛋白质丰度数据之间的一致性来量化蛋白质与蛋白质相互作用网络 (PPIN) 活动. 这个框架揭示了蛋白质相互作用在细胞过程中的功能意义.

更多相关视频

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.2K
Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
08:07

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

8.1K

相关实验视频

Last Updated: Jul 16, 2025

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
00:07

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

8.4K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.2K
Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
08:07

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

8.1K

科学领域:

  • 系统生物学 系统生物学
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 蛋白与蛋白相互作用 (PPI) 形成了细胞功能必不可少的生物分子网络.
  • 现有的PPI数据库缺乏关于特定细胞条件和表型的上下文.
  • 了解不同环境中的PPI活动对于破译细胞机制至关重要.

研究的目的:

  • 开发一个计算框架,ActivePPI,用于评估蛋白质-蛋白质相互作用网络 (PPIN) 活动.
  • 在各种细胞条件下量化PPIN架构和蛋白质测量数据之间的一致性.

主要方法:

  • 使用质谱数据,ActivePPI估计了蛋白质丰度概率密度.
  • 一种基于马尔科夫随机场的方法建模了PPIN.
  • 非参数变换测试推导经验P值来评估统计学意义.

主要成果:

  • ActivePPI有效地测量了PPIN和蜂环境之间的协议.
  • 该框架可实现网络活动评估,路径评估和网络优化.
  • 在广泛的数值实验中表现出卓越的性能.

结论:

  • ActivePPI是一个多功能工具,用于评估PPIN并揭示蛋白相互作用的功能意义.
  • 通过将网络活动与生物过程联系起来,提供对生理现象的洞察.
  • 有助于更深入地了解PPI在特定细胞环境中的功能.