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

Mesh Analysis01:20

Mesh Analysis

Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the power flow program computes the...
Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
Extended Versions of Green’s Theorem01:27

Extended Versions of Green’s Theorem

Green’s Theorem connects the circulation of a vector field around a closed curve with the behavior of the field across the region enclosed by that curve. It provides a way to replace a line integral around a boundary with a double integral over the interior region, making it especially useful in plane geometry, fluid flow, and vector calculus.Although Green’s Theorem is often introduced using simple regions without gaps, it can also be applied to regions made from several simple parts. This...
Vector Forms of Green’s Theorem01:26

Vector Forms of Green’s Theorem

The study of fluid motion often involves understanding how local rotational behavior relates to global circulation. In the context of a pond with pollutants, direct measurement of water movement along an irregular shoreline can be impractical. Green’s Theorem in vector form provides an alternative by relating the circulation around a closed boundary to properties of the flow within the enclosed region.Measurements of water velocity at different points define a continuous vector field that...
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...

You might also read

Related Articles

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

Sort by
Same author

Digital endpoints in clinical trials: building the business case for systematic adoption.

Nature reviews. Drug discovery·2026
Same author

SCREAM: Single-cell Clustering using Representation Autoencoder of Multiomics.

bioRxiv : the preprint server for biology·2025
Same author

Editor's Choice GlycoEnzDB: a database of enzymes involved in human glycosylation.

Glycobiology·2025
Same author

GlycoEnzDB: A database of enzymes involved in human glycosylation.

bioRxiv : the preprint server for biology·2025
Same author

Transformer-based Deep Learning for Glycan Structure Inference from Tandem Mass Spectrometry.

bioRxiv : the preprint server for biology·2025
Same author

Immune-mediated regeneration of cell-free vascular grafts in an ovine model.

NPJ Regenerative medicine·2025

Related Experiment Video

Updated: Jun 21, 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

Dynamical analysis of cellular networks based on the Green's function matrix.

Thanneer M Perumal1, Yan Wu, Rudiyanto Gunawan

  • 1Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, Singapore.

Journal of Theoretical Biology
|August 8, 2009
PubMed
Summary

This study introduces a Green's function matrix (GFM) method for analyzing cellular network dynamics. This dynamical analysis offers molecule-by-molecule insights into biological system behavior and signal propagation, aiding drug discovery.

More Related Videos

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Related Experiment Videos

Last Updated: Jun 21, 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

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Area of Science:

  • Systems Biology
  • Computational Biology
  • Mathematical Modeling

Background:

  • Cellular network complexity hinders intuitive understanding of functional regulations from static diagrams.
  • Ordinary differential equations (ODEs) are commonly used to model and simulate cellular network dynamics for biological insights.

Purpose of the Study:

  • To introduce a novel dynamical analysis method using Green's function matrix (GFM) for cellular network sensitivity analysis.
  • To provide molecule-by-molecule dynamical insights into system behavior and signal propagation, complementing classical parametric sensitivity analysis.

Main Methods:

  • Development and application of Green's function matrix (GFM) analysis for sensitivity coefficients with respect to initial concentrations.
  • Demonstration of the GFM method's efficacy on common network motifs and a specific biological model (Fas-induced programmed cell death).

Main Results:

  • GFM analysis provides dynamical, molecule-by-molecule insights into how cellular system behavior is achieved.
  • The method elucidates how impulse signals propagate through biological networks.
  • GFM analysis complements traditional parametric sensitivity approaches by offering a dynamical perspective.

Conclusions:

  • The GFM method offers a powerful approach for understanding complex cellular network dynamics.
  • Applications include model reduction, validation, and advancing drug discovery through target identification and optimization of therapeutic strategies.
  • The method is validated on network motifs and a programmed cell death model.