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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
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

6.3K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
6.3K
G Protein-coupled Receptors01:15

G Protein-coupled Receptors

12.3K
G Protein-Coupled Receptors or GPCRs are membrane-bound receptors that transiently associate with heterotrimeric G proteins and induce an appropriate response to sensory stimuli such as light, odors, hormones, cytokines, or neurotransmitters.
GPCRs are also called heptahelical, 7TM, or serpentine receptors, and consist of seven (H1-H7) transmembrane alpha-helices that span the bilayer to form a cylindrical core. The transmembrane helices are connected by three extracellular loops and three...
12.3K
Protein Organization01:24

Protein Organization

6.6K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
6.6K
Directing Proteins to the Rough Endoplasmic Reticulum01:34

Directing Proteins to the Rough Endoplasmic Reticulum

7.3K
The organelle-specific signaling sequences direct proteins synthesized in the cytosol to their final destination like ER, mitochondria, peroxisomes, etc. Some of the proteins directed to ER are then trafficked via vesicles to other organelles within the cell or the extracellular environment through the Golgi complex. For example, the rough ER synthesizes soluble proteins for transportation to the lysosomes or secretion out of the cell. It can also synthesize transmembrane proteins that can...
7.3K
Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

5.8K
Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
5.8K

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相关实验视频

Updated: Jul 24, 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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贝叶斯网络结构学习方法基于蛋白质信号网络的因果方向图.

Xiaohan Wei1, Yulai Zhang1, Cheng Wang1

  • 1School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China.

Entropy (Basel, Switzerland)
|July 8, 2023
PubMed
概括

这项研究引入了一种新的贝叶斯网络方法,用于蛋白质信号网络,提高因果关系的准确性,减少生物信息学应用的计算复杂性.

科学领域:

  • 生物信息学和计算生物学
  • 系统生物学 系统生物学
  • 网络科学 网络科学

背景情况:

  • 贝叶斯网络技术对于建模蛋白信号网络至关重要.
  • 现有的结构学习算法忽视了关键的因果关系,并面临高计算复杂性.
  • 对因果相互作用的准确建模对于理解细胞过程至关重要.

研究的目的:

  • 为蛋白质信号网络开发一个改进的贝叶斯网络结构学习方法.
  • 为了整合因果方向性和减少计算复杂性.
  • 提高网络推理的准确性和效率.

主要方法:

  • 变量之间的因果关系被计算并存储在图形矩阵中.
  • 一个连续优化问题是用配合损失和指向非循环先验来制定的.
  • 实施了裁剪程序,以确保学习网络结构的稀疏性.

主要成果:

  • 与现有方法相比,提出的方法显著改善了贝叶斯网络结构学习.
  • 在人工和真实生物数据集上观察到更高的准确性.
  • 实现了大量的计算负担的减少.

结论:

关键词:
贝叶斯网络是一个贝叶斯网络.因果的方向是因果的方向.蛋白质信号网络是蛋白质的信号网络.学习结构学习结构学习结构

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  • 这种新的方法有效地将因果推理集成到贝叶斯网络结构学习中,用于蛋白质信号通路.
  • 这种方法为生物信息学研究提供了更准确,更高效的计算替代方案.
  • 这些发现有助于更好地了解复杂的生物信号机制.