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

Constitutive and Regulated Gene Expression01:27

Constitutive and Regulated Gene Expression

Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the addition of a...
Cell Signaling Feedback Loops01:07

Cell Signaling Feedback Loops

Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
Negative feedback loops
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...

You might also read

Related Articles

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

Sort by
Same author

Retrospective analysis of age-specific non-pharmaceutical interventions on wild-type SARS-CoV-2 in Canada.

BMC public health·2026
Same author

Estimation of the exponential growth rate of an epidemic.

Infectious Disease Modelling·2026
Same author

Distributions of prevalence and daily new cases in a stochastic linear SEIR model.

Mathematical biosciences·2025
Same author

Estimating the effect of contact tracing during the early stage of an epidemic.

Infectious Disease Modelling·2025
Same author

A selfish supergene causes meiotic drive through both sexes in <i>Drosophila</i>.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

A mathematical model to assess the impact of testing and isolation compliance on the transmission of COVID-19.

Infectious Disease Modelling·2023

Related Experiment Video

Updated: May 10, 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

Sensitive dependence on initial conditions in gene networks.

A Machina1, R Edwards, P van den Driessche

  • 1Department of Mathematics and Statistics, University of Victoria, PO Box 3060, STN CSC, Victoria, British Columbia V8W 3R4, Canada. annama@uvic.ca

Chaos (Woodbury, N.Y.)
|July 5, 2013
PubMed
Summary
This summary is machine-generated.

Mathematical models of gene networks face challenges. This study reveals that gene regulation can lead to unpredictable system behavior, causing sensitivity to initial conditions and complex dynamics in gene networks.

More Related Videos

Sealable Femtoliter Chamber Arrays for Cell-free Biology
13:44

Sealable Femtoliter Chamber Arrays for Cell-free Biology

Published on: March 11, 2015

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression
11:23

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

Published on: October 6, 2019

Related Experiment Videos

Last Updated: May 10, 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

Sealable Femtoliter Chamber Arrays for Cell-free Biology
13:44

Sealable Femtoliter Chamber Arrays for Cell-free Biology

Published on: March 11, 2015

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression
11:23

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

Published on: October 6, 2019

Area of Science:

  • Systems Biology
  • Mathematical Biology
  • Computational Biology

Background:

  • Gene networks involve complex regulatory interactions between transcription factors.
  • Approximating sigmoidal gene interactions with step functions can lead to singular dynamics.
  • Singular perturbation methods are used to analyze systems with fast and slow dynamics.

Purpose of the Study:

  • To investigate the mathematical challenges in analyzing gene networks with competing regulation.
  • To explore the phenomenon of nonuniqueness in gene network models with limiting step-function interactions.
  • To analyze the behavior of realistic gene network models with smooth sigmoidal interactions.

Main Methods:

  • Analysis of singular perturbation theory.
  • Mathematical modeling of gene regulatory interactions.
  • Numerical simulations of gene network dynamics.

Main Results:

  • Nonuniqueness of solutions can arise in gene networks with limiting step-function interactions.
  • This nonuniqueness is distinct from Filippov solutions.
  • Smooth gene network models exhibit sensitivity to initial conditions, leading to interwoven basins of attraction.

Conclusions:

  • Gene network dynamics can be highly sensitive to initial conditions, especially in models with sigmoidal interactions.
  • The mathematical analysis of gene networks requires careful consideration of interaction functions and their approximations.
  • Understanding these complex dynamics is crucial for predicting gene network behavior.