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

8.9K
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...
8.9K
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
The Evidence for Evolution02:55

The Evidence for Evolution

48.4K
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
48.4K

You might also read

Related Articles

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

Sort by
Same author

Measurement of metacognition of emotional dimensions: a ROC based measurement method for metacognition of valence and arousal.

Frontiers in psychology·2026
Same author

LLM agents overcome the machine penalty when acting fairly but not when acting selfishly or altruistically.

National science review·2026
Same author

The attraction effect in perceptual decision-making: a case of dominance asymmetry.

Frontiers in psychology·2026
Same author

Regularities in temporal context influence the window of temporal integration.

Journal of vision·2025
Same author

Present-Focused Behavior as a Rational Adaptation to Precarity.

Open mind : discoveries in cognitive science·2025
Same author

Deciphering temporal scales of visual awareness: insights from flicker frequency modulation in continuous flash suppression.

Neuroscience of consciousness·2025

Related Experiment Video

Updated: Feb 13, 2026

Laparoscopy-endoscopy Cooperative Surgery for the Treatment of Gastric Gastrointestinal Stromal Tumors
05:16

Laparoscopy-endoscopy Cooperative Surgery for the Treatment of Gastric Gastrointestinal Stromal Tumors

Published on: February 19, 2022

6.6K

Evolution of Cooperation with Heterogeneous Conditional Cooperators.

Balaraju Battu1, V S Chandrasekhar Pammi2, Narayanan Srinivasan2

  • 1Centre of Behavioural and Cognitive Sciences, University of Allahabad, Allahabad, India. bala@cbcs.ac.in.

Scientific Reports
|March 16, 2018
PubMed
Summary
This summary is machine-generated.

Cooperation emerges in agent-based models when non-ideal agents, influenced by social information, occasionally deviate from strict rules. This leads to high cooperation rates in heterogeneous populations.

More Related Videos

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

6.8K
Mosaic Zebrafish Transgenesis for Functional Genomic Analysis of Candidate Cooperative Genes in Tumor Pathogenesis
09:45

Mosaic Zebrafish Transgenesis for Functional Genomic Analysis of Candidate Cooperative Genes in Tumor Pathogenesis

Published on: March 31, 2015

11.8K

Related Experiment Videos

Last Updated: Feb 13, 2026

Laparoscopy-endoscopy Cooperative Surgery for the Treatment of Gastric Gastrointestinal Stromal Tumors
05:16

Laparoscopy-endoscopy Cooperative Surgery for the Treatment of Gastric Gastrointestinal Stromal Tumors

Published on: February 19, 2022

6.6K
Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

6.8K
Mosaic Zebrafish Transgenesis for Functional Genomic Analysis of Candidate Cooperative Genes in Tumor Pathogenesis
09:45

Mosaic Zebrafish Transgenesis for Functional Genomic Analysis of Candidate Cooperative Genes in Tumor Pathogenesis

Published on: March 31, 2015

11.8K

Area of Science:

  • Evolutionary Game Theory
  • Agent-Based Modeling
  • Social Behavior

Background:

  • Conditional cooperation erodes with ideal agents in repeated interactions.
  • Rationality assumptions alone do not explain observed cooperation in human societies.

Purpose of the Study:

  • To propose a novel agent-based model incorporating social information for cooperation.
  • To investigate the role of non-ideal agents in establishing cooperation.

Main Methods:

  • Developed an evolutionary agent-based model with heterogeneous agents (ideal and non-ideal).
  • Agents use social information for stochastic donation decisions based on group donation levels.
  • Simulations controlled decision and selection intensities.

Main Results:

  • High cooperation levels (over 90%) were achieved with non-ideal agents under specific parameter ranges.
  • Emergence of cooperation requires both non-ideal agents and population heterogeneity.
  • The model emphasizes social information over individual agent history.

Conclusions:

  • Non-ideal agents are crucial for sustained cooperation in evolutionary models.
  • Social information, rather than individual history, can drive cooperation.
  • Heterogeneity and stochasticity are key factors in cooperation dynamics.