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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,...
Biological Causes of Schizophrenia01:29

Biological Causes of Schizophrenia

Schizophrenia, a severe psychiatric disorder, arises from a complex interplay of biological factors, including genetic predisposition, structural brain abnormalities, neurotransmitter dysregulation, and developmental irregularities. These factors collectively contribute to the onset and progression of the disorder, which typically manifests in late adolescence or early adulthood.
Genetic Factors in Schizophrenia
The genetic basis of schizophrenia is strongly supported by family and twin studies.
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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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...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Neuroplasticity01:01

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.

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Related Experiment Video

Updated: Jun 10, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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A strain-cue hypothesis for biological network formation.

Brian N Cox1

  • 1Teledyne Scientific Co. LLC, 1049 Camino Dos Rios, Thousand Oaks, CA 91360, USA. bcox@teledyne.com

Journal of the Royal Society, Interface
|July 31, 2010
PubMed
Summary

Cell migration and network formation are driven by external strain cues. This mechanism explains the development of complex biological networks, including neural and vascular systems.

Area of Science:

  • Biophysics
  • Developmental Biology
  • Cell Biology

Background:

  • Cell migration is crucial for development and disease.
  • Understanding the cues guiding cell movement and network formation is essential.
  • Existing models often lack a comprehensive explanation for emergent network structures.

Purpose of the Study:

  • To propose a unified biophysical model for cell migration and network formation.
  • To investigate the role of mechanical strain in guiding collective cell invasion.
  • To explain the emergence of complex network architectures, such as neural and vascular networks.

Main Methods:

  • A computational model simulating cell invasion and host medium deformation.
  • Analysis of strain fields generated by invading cell populations.

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  • Investigating the impact of strain magnitude versus strain gradients on network formation.
  • Parameter fitting to experimental data from neural network development.

    • Main Results:

    • External strain magnitude, not gradients, is sufficient to generate symmetric network structures.
    • The model predicts stabilization of branch formation and sprouting based on strain cues.
    • Network morphology is primarily controlled by the ratio of invader advance rate to host cell relaxation rate.
    • The model successfully replicates key geometrical features of the mouse gut neural network.

    Conclusions:

    • Collective cell invasion guided by external strain magnitude is a fundamental mechanism for network formation.
    • This strain-based mechanism can explain the development of diverse biological networks, including neural and vascular systems.
    • Intra-cell mechanisms regulating advance and relaxation rates are key determinants of network morphology.