Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Network Function of a Circuit

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.

Sequence Networks of Rotating Machines

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...

Fast Decoupled and DC Powerflow

Fast Decoupled and DC Powerflow

The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:

Block Diagram Reduction

Block Diagram Reduction

The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...

Signal Flow Graphs

Signal Flow Graphs

Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...

You might also read

Related Articles

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

Sort by

Same author

Beyond Boolean networks: new tools for the steady state analysis of multivalued networks.

ArXiv·2024

Same author

Digital twins in medicine.

Nature computational science·2024

Same author

Building digital twins of the human immune system: toward a roadmap.

NPJ digital medicine·2022

Same author

A modular computational framework for medical digital twins.

Proceedings of the National Academy of Sciences of the United States of America·2021

Same author

PlantSimLab - a modeling and simulation web tool for plant biologists.

BMC bioinformatics·2019

Same author

Tricuspid annular plane systolic excursion-to-aortic ratio provides a bodyweight-independent measure of right ventricular systolic function in dogs.

Journal of veterinary cardiology : the official journal of the European Society of Veterinary Cardiology·2018

Search research articles

Related Experiment Video

Updated: Jul 11, 2026

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

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

Published on: December 7, 2021

Reverse engineering of dynamic networks.

B Stigler¹, A Jarrah, M Stillman

¹Mathematical Biosciences Institute, The Ohio State University, Columbus USA.

Annals of the New York Academy of Sciences

|October 11, 2007

Summary

This study presents a new method for reverse-engineering biochemical networks. The algorithm identifies the most likely dynamic model from experimental data, improving understanding of gene regulatory networks.

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Jul 11, 2026

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

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

Published on: December 7, 2021

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Systems Biology
Computational Biology
Biophysics

Background:

Dynamic models are crucial for understanding biochemical networks.
Reverse-engineering these models from data is challenging.
Previous work identified network wiring diagrams.

Purpose of the Study:

To extend an algorithm for identifying minimal wiring diagrams.
To identify the most likely dynamic model fitting experimental data for a fixed wiring diagram.
To apply the method to simulated gene regulatory network data.

Main Methods:

Utilizing polynomial dynamic systems for modeling.
Extending an existing algorithm for network inference.
Applying the method to time-course data from Drosophila melanogaster.

Main Results:

The extended algorithm successfully identifies a most likely dynamic model.
The method demonstrates performance on simulated gene regulatory network data.
The approach refines the understanding of causal relationships in biological networks.

Conclusions:

The developed method enhances the reverse-engineering of dynamic biochemical models.
This approach provides a more complete model identification from experimental data.
The study contributes to the analysis of gene regulatory networks in model organisms.