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

Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

8.8K
Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
8.8K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

3.1K
3.1K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

2.7K
2.7K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

7.4K
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...
7.4K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

2.6K
2.6K
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

17.7K
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
17.7K

You might also read

Related Articles

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

Sort by
Same author

Dioscin suppresses colitis-associated colorectal tumorigenesis by inhibiting PPARγ-mediated fatty acid oxidation in TAMs.

International immunopharmacology·2026
Same author

Real-World Complication Profiles of Fully and Semi-Implanted Intrathecal Drug Delivery Systems for Cancer Pain: A Large Single-Center Chinese Cohort.

Pain and therapy·2026
Same author

1,2,4-Triazolium compounds as anti-oomycete leads against Phytophthora capsici.

Pest management science·2026
Same author

OTULIN protects hyperoxia-induced neonatal lung injury and modulates mitochondrial protein OPA1 in association with the E3 ubiquitin ligase RNF31.

Cellular & molecular biology letters·2026
Same author

Decoding the temporal regulome of wheat starch: Wx allelic hierarchy unveils novel negative regulators.

Carbohydrate polymers·2026
Same author

Multi-Responsive SEBS/MXene Janus Membranes Enabling Piezoelectric Energy Harvesting, Humidity Sensing, and Infrared Stealth.

Nano-micro letters·2026

Related Experiment Video

Updated: Feb 5, 2026

Determining the Mechanical Strength of Ultra-Fine-Grained Metals
05:04

Determining the Mechanical Strength of Ultra-Fine-Grained Metals

Published on: November 22, 2021

2.6K

Boosting Cooperative Coevolution for Large Scale Optimization With a Fine-Grained Computation Resource Allocation

Zhigang Ren, Yongsheng Liang, Aimin Zhang

    IEEE Transactions on Cybernetics
    |September 6, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a fine-grained computation resource allocation (FCRA) strategy for cooperative coevolution (CC) algorithms. FCRA optimizes resource use in large-scale optimization problems, significantly outperforming existing methods.

    More Related Videos

    Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction
    09:13

    Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction

    Published on: April 1, 2017

    14.2K
    Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography
    09:00

    Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography

    Published on: September 29, 2019

    13.8K

    Related Experiment Videos

    Last Updated: Feb 5, 2026

    Determining the Mechanical Strength of Ultra-Fine-Grained Metals
    05:04

    Determining the Mechanical Strength of Ultra-Fine-Grained Metals

    Published on: November 22, 2021

    2.6K
    Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction
    09:13

    Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction

    Published on: April 1, 2017

    14.2K
    Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography
    09:00

    Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography

    Published on: September 29, 2019

    13.8K

    Area of Science:

    • Optimization Algorithms
    • Computational Intelligence

    Background:

    • Cooperative coevolution (CC) is effective for large-scale optimization problems (LSOPs).
    • Traditional CC algorithms often waste computation resources (CR) due to uniform allocation.
    • Existing contribution-based CC algorithms offer improvements but lack a rigorous mathematical model for CR allocation.

    Purpose of the Study:

    • To develop a novel, fine-grained computation resource allocation (FCRA) strategy for CC algorithms.
    • To mathematically model the CR allocation (CRA) problem within CC.
    • To enhance the efficiency and performance of CC in solving LSOPs.

    Main Methods:

    • Developed a mathematical model for the CRA problem in CC.
    • Proposed a fine-grained CRA (FCRA) strategy considering optimal solutions and CC evolution.
    • FCRA allocates CR at the iteration level, prioritizing subproblems with the highest estimated contribution.
    • Integrated FCRA with success-history-based adaptive differential evolution (SHADE).

    Main Results:

    • FCRA significantly outperforms existing CRA strategies.
    • The CC algorithm integrated with FCRA demonstrates high competitiveness in solving LSOPs.
    • Experimental results on benchmark suites validate the efficiency of FCRA.

    Conclusions:

    • FCRA offers a superior approach to CR allocation in CC algorithms.
    • The proposed strategy effectively addresses resource waste in traditional CC.
    • This work advances the application of CC for solving complex large-scale optimization problems.