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相关概念视频

Protein Networks02:26

Protein Networks

3.9K
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,...
3.9K
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
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

6.8K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
6.8K

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相关实验视频

Updated: Jun 17, 2025

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

Published on: October 19, 2021

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在指导概率生物学网络中识别关键控制蛋白的实际有效算法.

Yusuke Tokuhara1, Tatsuya Akutsu2, Jean-Marc Schwartz3

  • 1Department of Information Science, Faculty of Science, Toho University, Funabashi, Chiba, Japan.

NPJ systems biology and applications
|August 12, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的算法,用于识别具有不确定的相互作用的复杂生物网络中的关键控制节点. 该方法有效地找到驱动网络功能的关键分子,帮助疾病研究.

更多相关视频

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

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mRNA Interactome Capture from Plant Protoplasts
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mRNA Interactome Capture from Plant Protoplasts

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相关实验视频

Last Updated: Jun 17, 2025

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

Published on: October 19, 2021

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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

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mRNA Interactome Capture from Plant Protoplasts
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mRNA Interactome Capture from Plant Protoplasts

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科学领域:

  • 系统生物学 系统生物学
  • 网络科学 网络科学
  • 计算生物学 计算生物学

背景情况:

  • 网络可控性将控制理论与生物系统的网络结构相结合.
  • 识别关键节点对于理解网络控制至关重要,但现有的方法在概率交互方面存在困难.

研究的目的:

  • 开发一种有效的算法,用于确定概率定向网络中的关键控制节点.
  • 将分子相互作用的概率性整合到网络控制模型中.

主要方法:

  • 开发了一个基于最小主导集合框架的概率控制模型.
  • 创建了数学工具,以提高在大型网络中确定关键控制节点的效率.

主要成果:

  • 该算法有效地识别了概率定向网络中的关键控制节点.
  • 应用于人类细胞内信号传导网络,将关键节点与疾病相关的基因联系起来,包括SARS-CoV-2的目标.

结论:

  • 拟议的方法提供了一种实用和有效的方式来分析概率生物学网络中的关键控制节点.
  • 这种方法可以推进各种生物系统的研究,其中的相互作用不确定或概率.