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.

Pole and System Stability

Pole and System Stability

The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's response.

Transformations of Functions III

Transformations of Functions III

Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...

Control System Problem

Control System Problem

In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...

Transformations of Functions I

Transformations of Functions I

A function's graph can be modified by changing its position or size without altering its overall shape. These transformations allow the graph to be moved across the coordinate plane while preserving its pattern and structure. One of the most common transformations is shifting, which repositions the graph without distorting it.When the output of a function is adjusted by adding or subtracting a constant, the graph shifts vertically. A positive value moves the graph upward, while a negative value...

Transformations of Functions II

Transformations of Functions II

Transformations in mathematics alter the position or orientation of a function’s graph while preserving its fundamental shape. One important type of transformation is the horizontal shift, which involves modifying the input variable within a function’s equation. This operation affects where outputs occur along the horizontal axis but does not alter the function’s overall structure.A horizontal shift is achieved by replacing the input variable x with either x + c or x - c, where c is a constant.

You might also read

Related Articles

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

Sort by

Same author

Relationships Between Leaf Coloration Changes, Cellular Structure, Photosynthetic Physiology, and Hydraulic Traits in <i>Liquidambar formosana</i> Hance Under Drought Stress in Autumn.

Plants (Basel, Switzerland)·2026

Same author

Device failures and patient adverse events from EUS: 26-year FDA MAUDE analysis (2000-2025).

Endoscopic ultrasound·2026

Same author

Methylome and Transcriptome Analysis Reveals Differences in Callus Development and Plantlet Regeneration Capacity Between Two <i>Eucalyptus</i> Species.

Plants (Basel, Switzerland)·2026

Same author

A key role of Canoe's intrinsically disordered region in linking cell junctions to the cytoskeleton.

The Journal of cell biology·2025

Same author

Effects of pulse indicated continuous cardiac output monitoring on outcomes of intensive care unit patients with shock: a propensity score matching analysis.

World journal of emergency medicine·2025

Same author

Beverages intake among women of childbearing age from 1990 to 2018: Global Dietary Database findings.

Nutrition (Burbank, Los Angeles County, Calif.)·2025

Search research articles

Related Experiment Video

Updated: Jul 16, 2026

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

The impact of function perturbations in Boolean networks.

Yufei Xiao¹, Edward R Dougherty

¹Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX 77843, USA.

Bioinformatics (Oxford, England)

|March 24, 2007

Summary

This study investigates function perturbations in Boolean networks, offering methods to predict their impact and synthesize desired network behaviors. These findings enable targeted interventions for disease treatment and gene network analysis.

Related Experiment Videos

Last Updated: Jul 16, 2026

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

Area of Science:

Systems Biology
Computational Biology
Network Science

Background:

Network robustness is crucial for stability but hinders targeted interventions.
Boolean networks are models where robustness can be state or structure-based.
Function perturbations in Boolean networks present both analytical and synthetic challenges.

Purpose of the Study:

To explore the impact of function perturbations in Boolean networks.
To develop analytical methods for predicting effects on network dynamics and attractors.
To create synthetic approaches for modifying network characteristics via function changes.

Main Methods:

Analytical approaches to predict impacts of function perturbations on network state transitions and attractors.
Identification of perturbations by observing their consequences on network behavior.
Synthesis methods to judiciously alter network functions for desired characteristics, especially attractors.

Main Results:

Demonstrated analytical and synthetic strategies for managing function perturbations in Boolean networks.
Applied intervention procedures to a WNT5A network to mitigate melanoma metastasis risk.
Utilized identification procedures on a Drosophila melanogaster gene network to pinpoint regulatory function perturbations.

Conclusions:

Function perturbations in Boolean networks can be analyzed and synthesized for specific outcomes.
This framework supports targeted network interventions for biological applications, such as disease treatment.
The methods facilitate the identification of causative perturbations in complex biological systems.