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

PD Controller: Design01:26

PD Controller: Design

547
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
547
Gradient and Del Operator01:14

Gradient and Del Operator

4.2K
In mathematics and physics, the gradient and del operator are fundamental concepts used to describe the behavior of functions and fields in space. The gradient is a mathematical operator that gives both the magnitude and direction of the maximum spatial rate of change. Consider a person standing on a mountain. The slope of the mountain at any given point is not defined unless it is quantified in a particular direction. For this reason, a "directional derivative" is defined, which is a vector...
4.2K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

322
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
322
Feedback control systems01:26

Feedback control systems

635
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
635
PI Controller: Design01:24

PI Controller: Design

1.1K
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
1.1K
Controller Configurations01:22

Controller Configurations

302
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
302

You might also read

Related Articles

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

Sort by
Same author

Evolvability in vertebrate segmentation.

Seminars in cell & developmental biology·2025
Same author

From genes to patterns: five key dynamical systems concepts to decode developmental regulatory mechanisms.

Development (Cambridge, England)·2025
Same author

Modularity of the segmentation clock and morphogenesis.

eLife·2025
Same author

Approximated gene expression trajectories for gene regulatory network inference on cell tracks.

iScience·2024
Same author

A whole-body micro-CT scan library that captures the skeletal diversity of Lake Malawi cichlid fishes.

Scientific data·2024
Same author

Naturalizing relevance realization: why agency and cognition are fundamentally not computational.

Frontiers in psychology·2024
Same journal

Building a resilient ovarian reserve: Early soma-oocyte interactions.

Current topics in developmental biology·2026
Same journal

Role of macrophages in testis function.

Current topics in developmental biology·2026
Same journal

Role of retinoic acid in meiosis.

Current topics in developmental biology·2026
Same journal

Impact of cancer immunotherapies on oocyte health and ovarian function.

Current topics in developmental biology·2026
Same journal

The ovarian stroma as a key regulator of follicular development and gamete quality across the reproductive lifespan.

Current topics in developmental biology·2026
Same journal

Intercellular cyclic nucleotide dynamics mediate oocyte meiosis in mammalian preovulatory follicles.

Current topics in developmental biology·2026
See all related articles

Related Experiment Video

Updated: Dec 26, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.0K

Dynamic positional information: Patterning mechanism versus precision in gradient-driven systems.

Johannes Jaeger1, Berta Verd2

  • 1Complexity Science Hub (CSH), Vienna, Austria; Department of Molecular Evolution & Development, University of Vienna, Vienna, Austria.

Current Topics in Developmental Biology
|March 8, 2020
PubMed
Summary
This summary is machine-generated.

This study defines "positional information" in developmental biology using two distinct frameworks: Shannon information for decoding and error analysis, and general relativistic information for assessing pattern formation output. Combining these concepts enhances mechanistic understanding of robust biological patterning.

Keywords:
Dynamical systemsInformation theoryMechanismPatterning precisionPositional information

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.5K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.2K

Related Experiment Videos

Last Updated: Dec 26, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.0K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.5K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.2K

Area of Science:

  • Developmental Biology
  • Systems Biology
  • Theoretical Biology

Background:

  • The concept of
  • information
  • in biology, particularly
  • positional information
  • , is crucial for understanding pattern formation but lacks precise definition.
  • Morphogen gradients are key to establishing patterns during development.
  • Existing definitions of positional information are often ambiguous.

Purpose of the Study:

  • To provide two precise, alternative interpretations of
  • positional information
  • in developmental biology.
  • To explore the complementary uses of Shannon information and general relativistic positional information.
  • To offer a combined framework for a mechanistic understanding of robust pattern formation.

Main Methods:

  • Conceptual analysis of
  • information theory
  • applied to biological patterning.
  • Formulation of positional information using Shannon information metrics.
  • Development of a general relativistic framework for positional information.

Main Results:

  • Positional information defined as Shannon information elucidates decoding processes and error propagation in patterning systems.
  • General relativistic positional information offers a metric to evaluate the fidelity of pattern-forming mechanisms.
  • Both interpretations are non-competing and provide distinct, valuable insights.

Conclusions:

  • A dual approach, integrating Shannon information and general relativistic positional information, provides a comprehensive understanding of biological pattern formation.
  • This combined conceptual framework is essential for a mechanistic grasp of robust developmental patterning.
  • Precise definitions of information are vital for advancing developmental biology research.