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Related Concept Videos

Protein Networks02:26

Protein Networks

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,...
Protein Networks02:26

Protein Networks

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,...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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...
IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the  phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and produces two-second...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
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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

Nucleation pathways on complex networks.

Chuansheng Shen1, Hanshuang Chen, Miaolin Ye

  • 1Hefei National Laboratory for Physical Sciences at Microscales, and Department of Chemical Physics, University of Science and Technology of China, Hefei 230026, China.

Chaos (Woodbury, N.Y.)
|April 6, 2013
PubMed
Summary

This study reveals distinct nucleation pathways in the Ising model across different network structures. Heterogeneous networks exhibit unique cluster merging dynamics compared to homogeneous ones, driven by network heterogeneity.

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Area of Science:

  • Statistical Mechanics
  • Computational Physics
  • Network Science

Background:

  • Understanding first-order phase transitions is crucial in various natural systems.
  • The kinetics of nucleation are heavily influenced by the underlying system's structure.
  • Network topology plays a significant role in nucleation processes.

Purpose of the Study:

  • To investigate the nucleation pathway of the Ising model in homogeneous and heterogeneous networks.
  • To elucidate how network topology affects the kinetics and mechanisms of nucleation.
  • To compare nucleation routes in networks with varying degree-mixing properties.

Main Methods:

  • Utilized the forward flux sampling (FFS) method for simulating nucleation.
  • Analyzed the Ising model on different network topologies (homogeneous and heterogeneous).
  • Examined the properties and evolution of nucleating clusters throughout the process.

Main Results:

  • Nucleation pathways show distinct features dependent on network topology.
  • Homogeneous networks feature a dominant cluster gradually accreting smaller clusters.
  • Heterogeneous networks display early emergence of small clusters that merge sharply to form the critical nucleus.

Conclusions:

  • Network heterogeneity is the primary driver of differing nucleation pathways.
  • The distinct cluster dynamics observed highlight the impact of network structure on phase transition kinetics.
  • Forward flux sampling effectively captures topological influences on nucleation mechanisms.