Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

8.5K
When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
8.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mechanisms and implications of high depolarization baseline offsets in conductance-based neuronal models.

Journal of neurophysiology·2025
Same author

Discriminating neural ensemble patterns through dendritic computations in randomly connected feedforward networks.

eLife·2025
Same author

Mathematical basis and toolchain for hierarchical optimization of biochemical networks.

PLoS computational biology·2024
Same author

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows.

eLife·2022
Same author

Adult brain neurons require continual expression of the schizophrenia-risk gene Tcf4 for structural and functional integrity.

Translational psychiatry·2021
Same author

Correction: Precise excitation-inhibition balance controls gain and timing in the hippocampus.

eLife·2021

Related Experiment Video

Updated: Jul 11, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K

Understanding molecular signaling cascades in neural disease using multi-resolution models.

Nisha Ann Viswan1, Upinder Singh Bhalla2

  • 1National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road, Bengaluru, 560065, India; The University of Trans-Disciplinary Health Sciences and Technology, Bangalore, India. Electronic address: https://twitter.com/nishanna.

Current Opinion in Neurobiology
|November 16, 2023
PubMed
Summary
This summary is machine-generated.

Signaling networks execute cellular programs, but their complexity can lead to disease. Computational models are essential for understanding these networks in health and illness.

More Related Videos

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.8K
Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro
16:13

Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro

Published on: June 13, 2011

20.1K

Related Experiment Videos

Last Updated: Jul 11, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.8K
Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro
16:13

Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro

Published on: June 13, 2011

20.1K

Area of Science:

  • Neuroscience
  • Computational Biology
  • Systems Biology

Background:

  • Cellular functions are executed by signaling networks, which involve complex cascades of events.
  • Neuronal function, especially at the synapse, heavily relies on these signaling pathways.
  • Dysfunction in signaling cascades can result in various diseases with diverse phenotypes.

Purpose of the Study:

  • To explore the construction and application of computational models for understanding cellular signaling.
  • To highlight the necessity of computational models in managing the complexity of signaling pathways.
  • To demonstrate the advantages of employing multiple models at varying levels of detail.

Main Methods:

  • Review of computational modeling approaches for biological systems.
  • Analysis of signaling pathways across different biological scales (milliseconds to lifetime).
  • Discussion on integrating diverse modeling strategies.

Main Results:

  • Computational models are crucial tools for dissecting complex signaling networks.
  • Families of models offer a comprehensive approach to studying signaling in both health and disease.
  • Modeling aids in understanding the link between signaling dysregulation and disease phenotypes.

Conclusions:

  • Computational modeling is indispensable for unraveling the intricacies of cellular signaling.
  • A multi-model approach provides deeper insights into signaling network dynamics.
  • Understanding signaling networks through modeling is key to addressing related diseases.