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Related Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
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,...
Circuit Terminology01:14

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
A circuit, on the other hand, is also an interconnected system of electrical elements but must contain one or more closed paths.
Electrical Synapses01:28

Electrical Synapses

Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...

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Related Experiment Video

Updated: Jun 29, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Sequence nets.

Jie Sun1, Takashi Nishikawa, Daniel Ben-Avraham

  • 1Department of Mathematics & Computer Science, Clarkson University Potsdam, New York 13699-5815, USA. sunj@clarkson.edu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 15, 2008
PubMed
Summary
This summary is machine-generated.

We introduce sequence nets, a new class of complex networks generated from letter sequences. These networks offer modular structures and analytical tractability, enhancing the modeling of real-world systems.

Related Experiment Videos

Last Updated: Jun 29, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Area of Science:

  • Network Science
  • Complex Systems Analysis
  • Computational Modeling

Background:

  • Threshold networks, generated from binary alphabets, exhibit modularity and analytical tractability.
  • Real-world complex networks often display modular structures similar to those found in threshold nets.

Purpose of the Study:

  • To introduce and classify a novel class of networks, termed sequence nets, generated by letter sequences.
  • To explore the analytical properties and modeling capabilities of these sequence nets.
  • To compare sequence nets with existing threshold network models.

Main Methods:

  • Generating networks using sequences from a finite alphabet (m letters) and predefined connectivity rules.
  • Applying symmetry principles for a comprehensive classification of two- and three-letter sequence nets.
  • Analyzing network properties such as degree distribution, shortest paths, and betweenness centrality.

Main Results:

  • Discovery of two distinct classes within two-letter sequence nets.
  • Demonstration that sequence nets retain desirable analytical properties of threshold nets.
  • Identification of richer modeling possibilities for complex networks using sequence nets.

Conclusions:

  • Sequence nets provide a flexible framework for constructing complex networks with inherent modularity.
  • These networks offer enhanced capabilities for modeling diverse real-world systems compared to traditional threshold nets.
  • The analytical tractability of sequence nets facilitates deeper understanding of network structures and functions.