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

Combinatorial Gene Control02:33

Combinatorial Gene Control

8.6K
Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
8.6K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

438
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
438
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

6.0K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
6.0K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

1.8K
1.8K
Root Loci for Positive-Feedback Systems01:23

Root Loci for Positive-Feedback Systems

471
The Hartley oscillator is a positive feedback system that sustains oscillations by feeding the output back to the input in phase, thereby reinforcing the signal. Positive feedback systems can be viewed as negative feedback systems with inverted feedback signals. In these systems, the root locus encompasses all points on the s-plane where the angle of the system transfer function equals 360 degrees.
The construction rules for the root locus in positive feedback systems are similar to those in...
471
Operon Model01:23

Operon Model

2.5K
The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...
2.5K

You might also read

Related Articles

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

Sort by
Same author

Genome-Wide Association Study of Gross Hair Weight and Hair Length Traits in Different Body Regions of Tianzhu White Yak.

Biomolecules·2026
Same author

Effects of dietary supplementation with astragalus polysaccharides on growth performance, serum parameters, and rumen microbial function of yaks.

BMC microbiology·2025
Same author

The High-Altitude Adaptation Characteristics of Microbiota-Host Cross-Talk in Yak Gastrointestinal Track.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

The distribution of D-amino acid in food and drug and their effects on mouse metabolism.

Journal of pharmaceutical and biomedical analysis·2025
Same author

Online determination of elements in pure iron by non-weighing micro-reaction with inductively coupled plasma optical emission spectrometry.

Analytica chimica acta·2025
Same author

Polymorphisms of <i>TXK</i> and <i>PLCE1</i> Genes and Their Correlation Analysis with Growth Traits in Ashidan Yaks.

Animals : an open access journal from MDPI·2024
Same journal

Thymidylate synthase inhibitory drugs induce p53-dependent pathways differently.

PloS one·2026
Same journal

Top-down and bottom-up attention for joint pattern classification and reconstruction.

PloS one·2026
Same journal

Short- and long-term scaling behavior of blood pressure and pulse arrival time during sleep in healthy controls and patients with obstructive sleep apnea.

PloS one·2026
Same journal

Double DQN-based secrecy energy efficiency and fairness performance in IRS-assisted NOMA systems with friendly jamming.

PloS one·2026
Same journal

10 recommendations for strengthening citizen science for improved societal and ecological outcomes: A co-produced analysis of challenges and opportunities in the 21st century.

PloS one·2026
Same journal

Paying in public: Peer effects, impression management, and willingness to pay on digital payment platforms.

PloS one·2026
See all related articles

Related Experiment Video

Updated: May 1, 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

1.7K

A parallel attractor-finding algorithm based on Boolean satisfiability for genetic regulatory networks.

Wensheng Guo1, Guowu Yang2, Wei Wu3

  • 1School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China; Electrical Engineering Department, University of California Los Angeles, Los Angeles, California, United States of America.

Plos One
|April 11, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel algorithm for finding attractors in Boolean networks, crucial for understanding genetic regulatory networks. The method improves performance on complex networks and offers parallel computing scalability.

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.0K
Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
10:46

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

Published on: October 18, 2022

1.9K

Related Experiment Videos

Last Updated: May 1, 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

1.7K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.0K
Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
10:46

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

Published on: October 18, 2022

1.9K

Area of Science:

  • Computational Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Dynamic analysis is increasingly vital in biological systems.
  • Boolean networks are standard models for genetic regulatory networks.
  • Identifying attractors in state transition graphs is a key challenge.

Purpose of the Study:

  • To propose a novel algorithm for attractor finding in Boolean networks.
  • To address the complexity of modern genetic regulatory networks.
  • To develop a scalable solution for attractor identification.

Main Methods:

  • Modeled genetic regulatory networks as Boolean networks.
  • Partitioned networks into blocks based on strongly connected components and gradients.
  • Defined decision nodes for inter-block connections.
  • Utilized satisfiability solving on decision nodes to identify attractors.

Main Results:

  • The proposed algorithm matches existing methods on small networks.
  • It outperforms existing algorithms on larger, more complex networks.
  • Demonstrated good scalability on parallel computing architectures.

Conclusions:

  • The novel algorithm effectively identifies attractors in Boolean networks.
  • It offers superior performance for complex genetic regulatory network analysis.
  • The algorithm's parallelizability is advantageous for future research.