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52 results for “evolution of cooperation”
Kin selection explains the evolution of cooperation in the gut microbiota, by Simonet & McNally, 2020, Dataset S1 and codes for statistical analysis and figures production
<p>Dataset S1 contains all raw and processed material referred to in the published article "Kin selection explains the evolution of cooperation in the gut microbiota". R codes files provide all codes to replicate the analysis. Please refer to the README file for a description of all code files. The manifest files are those obtained by accessing the HMP portal on April 2020 under Project > HMP, Body Site > feces, Studies>WGS-PP1, File Type > WGS raw sequences set, File format > FASTQ.</p> <p>We also provide access to these data and codes at our GitHub (https://github.com/CamilleAnna/HamiltonRuleMicrobiome gitRepos.git) which can be cloned to directly re-run this analysis. </p> <p><strong>Legends for Dataset S1:</strong></p> <ul> <li>Sheet 1: Metagenomic samples used and access links.</li> <li>Sheet 2: Reference on bacterial cooperation retrieved from Web of Science search: TI¯((microb* OR bacter* OR microorganis* OR micro-organis*) AND (coop* OR social*)</li> <li>Sheet 3: Retained bacteria cooperation keywords</li> <li>Sheet 4: GOs identified by annotating all MIDAS database genomes (5944 genomes) with PANNZER2.</li> <li>Sheet 5: Full list of potential bacterial cooperation GO terms and description of manual curation decisions.</li> <li>Sheet 6: Final list of bacterial cooperation GO used for the analysis</li> <li>Sheet 7: Genomic diversity of the bacterial population within and across host. Computed from MIDAS snp_diversity.py pipeline.</li> <li>Sheet 8: final dataset for statistical analysis.</li> <li>Sheet 9: per-gene annotation of cooperation.</li> </ul>
Model, data, and analysis for Negative Niche Construction Favors the Evolution of Cooperation
<p>This repository contains the model, data, and analysis corresponding to <em>Negative Niche Construction Favors the Evolution of Cooperation</em> as submitted for review by Brian D. Connelly, Katherine J. Dickinson, Sarah P. Hammarlund, and Benjamin Kerr. Contents are released to the public domain under the Creative Commons CC0 License.</p>
Model, Data, and Analysis Scripts for The Evolution of Cooperation by the Hankshaw Effect
<p>Model, Data, and Analysis Scripts for The Evolution of Cooperation by the Hankshaw Effect as submitted</p>
Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions
<p>The question of how cooperation evolves and is sustained over time has been a long-standing and unresolved issue in the fields of evolutionary biology and social sciences. Previous theoretical and experimental research based on the collective-risk social dilemma game has revealed the risk that the failure of collective goals will affect the evolution of cooperation. Considering that in the real world individuals usually adjust their decisions based on environmental factors such as risk intensity and cooperation level, it is still not well understood how such conditional behaviors affect the evolution of cooperation in repeated group interactions scenario from a theoretical perspective. Here, we construct an evolutionary game model with repeated interactions, in which defectors decide whether to cooperate in subsequent rounds of the game based on whether the risk exceeds their tolerance threshold and whether the number of cooperators exceeds the collective goal in the early rounds of the game. We find that the introduction of conditional cooperation strategy can effectively promote the emergence of cooperation, especially when the risk is low. In addition, the risk threshold significantly affects the evolutionary outcomes. Furthermore, our results confirm that a high risk can promote the emergence of cooperation. Importantly, when the risk exceeds the tolerance threshold, timely adjustment of strategies by conditional cooperators is beneficial for maintaining high-level cooperation.</p>
Dataset for Evolution of Cooperation in Costly Institutions: Red Queen and Black Queen Dynamics in Heterogenous Public Goods
<p>This dataset contains the Matlab codes used in "Evolution of Cooperation in Costly Institutions: Red Queen and Black Queen Dynamics in Heterogenous Public Goods".</p> <p>The zip file contains Matlab codes used in simulation and numerical solutions of the replicator dynamics. The zip file "Figures" contains the Matlab code and data used to produce figures in this study.</p>
Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions
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Genetic architecture promotes the evolution and maintenance of cooperation
<p>Code and data for Frenoy et al 2013 ("Genetic Architecture Promotes the Evolution and Maintenance of Cooperation" in PLoS Computational Biology)</p>
Model, configuration, data, and analysis scripts for The Evolution of Cooperation by the Hankshaw Effect
<p>Computational model, configuration files, result data, and analysis scripts for The Evolution of Cooperation by the Hankshaw Effect as published in Evolution (doi: 10.1111/evo.12928)</p>
Asynchronous updates can promote the evolution of cooperation on multiplex networks
<p>Code is included to run the model described for varying enhancement factors, and the different versions of the social dilemmas (public goods game and prisoners dilemma) described in the publication. Code is also included to calculate the payoff probabilities described in the publication. The data used to plot the mean cooperation against the enhancement factors is also included for each of the models permutations. Which code files are for which permutation are described in the accompanying pdf.</p>
Data for: Evolution Reinforces Cooperation with the Emergence of Self-Recognition Mechanisms: an empirical study of the Moran process for the iterated Prisoner's dilemma using reinforcement learning
<p>This contains data used for a paper titled: Evolution Reinforces Cooperation with the Emergence of Self-Recognition Mechanisms: an empirical study of the Moran process for the iterated Prisoner's dilemma using reinforcement learning.</p> <p>Numerous data sets are included, the main being `main.csv` which includes the fixation counts for a number of Moran processes between pairs of players from the Axelrod library.</p> <p>The source code and explanation of the data is here: https://github.com/Axelrod-Python/axelrod-moran. </p> <p> </p>
Python code generating the data of figures 2, 3, 4, 5 and 6 of the manuscript: The evolution of cooperation in the unidirectional linear division of labour of finite roles
<p>The evolution of cooperation is an unsolved mystery, which we see in many social and biological systems. In the study titled "The evolution of cooperation in the unidirectional linear division of labour of finite roles", we investigate under which sanction systems and how the evolution of cooperation happens in the linear division of labour. </p> <p>This python code has been used to produce the results of Figures 2, 3, 4, 5, and 6 of the manuscript. This code shows the evolution of cooperation among the population of various different groups which have different roles to play in the linear division of labour, on the basis of numerical analysis of a partial differential equation system, which originates from the replicator equations used in the evolutionary game theory. We find the locally stable equilibria using this code, which shows the ultimate results of the dynamics in the system under given parameters. Figures 3, 5, and 6 are direct products of the code, showing the dynamics of a system, and figures 2 and 4 are the end results of those dynamics. </p> <p>We found that in a social dilemma situation, cooperation never evolves in the system without punishment. However, with sanction systems by introducing a suitable amount of punishment, while having a suitable findability of the defector, and a suitable initial population structure, cooperation can evolve. These results can be found with this code. We have no legal or ethical concerns regarding this data as this is a numerical analysis based on theoretical equations. </p>
Data from: Phenotypic plasticity of antibiotic resistance, metabolism byproduct utilization and the evolution of mutually beneficial cooperation in Escherichia coli
<p><span>Although tag-based donation and recognition have well explained how the cooperative individuals are positively assorted if the cooperative individuals possess some signals and are also able to detect such signals, an additional mechanism is required to explain why some individuals pay the costs of evolving such a tag that may not be rewarded subsequently, and how such tag-based cooperative individuals will meet other similar individuals with a very low mutation rate. Here, we show that many and even all<em> Escherichia coli </em>bacteria cells in the increased antibiotic concentration will plastically evolve to be antibiotic resistant individuals who could protect antibiotic sensitive strain from the attack of antibiotics, and the antibiotic resistant strain could reversibly evolve to be antibiotic sensitive in non-antibiotic supplement medium but in a harsher environment with low glucose. A further experiment showed that antibiotic-sensitive <em>E. coli </em>strain could in turn help reduce the concentration of indole produced by the resistant strain. This metabolic product is harmful to the growth of the antibiotic-resistant strain but benefits the antibiotic-sensitive strain by helping turn on the multi-drug exporter to discharge the antibiotic. The utilization of metabolism byproduct indole produced by antibiotic-resistant cells benefits antibiotic-sensitive cells, while the indole-absorbing service of antibiotic sensitive cells unconsciously help in nullifying the indole side effect on antibiotic resistant strain, and a mutual benefit cooperation could therefore evolve.</span></p>
Data from: Phenotypic plasticity of antibiotic resistance, metabolism byproduct utilization and the evolution of mutually beneficial cooperation in Escherichia coli
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Python code generating the data of figures 2, 3, 4, 5 and 6 of the manuscript: The evolution of cooperation in the unidirectional linear division of labour of finite roles
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Metabolic byproduct utilization and the evolution of mutually beneficial cooperation in Escherichia coli
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Data from: Resource heterogeneity and the evolution of public-goods cooperation
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Data from: Evolution of altruistic cooperation among nascent multicellular organisms
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Data from: Using text-mined trait data to test for cooperate-and-radiate co-evolution between ants and plants
Mutualisms may be "key innovations" that spur lineage diversification by augmenting niche breadth, geographic range, or population size, thereby increasing speciation rates or decreasing extinction rates. Whether mutualism accelerates diversification in both interacting lineages is an open question. Research suggests that plants that attract ant mutualists have higher diversification rates than non-ant associated lineages. We ask whether the reciprocal is true: does the interaction between ants and plants also accelerate diversification in ants, i.e. do ants and plants cooperate-and-radiate? We used a novel text-mining approach to determine which ant species associate with plants in defensive or seed dispersal mutualisms. We investigated patterns of lineage diversification across a recent ant phylogeny using BiSSE, BAMM, and HiSSE models. Ants that associate mutualistically with plants had elevated diversification rates compared to non-mutualistic ants in the BiSSE model, with a similar trend in BAMM, suggesting ants and plants cooperate-and-radiate. However, the best-fitting model was a HiSSE model with a hidden state, meaning that diversification models that do no account for unmeasured traits are inappropriate to assess the relationship between mutualism and ant diversification. Against a backdrop of diversification rate heterogeneity, the best-fitting HiSSE model found that mutualism actually decreases diversification: mutualism evolved much more frequently in rapidly diversifying ant lineages, but then subsequently slowed diversification. Thus, it appears that ant lineages first radiated, then cooperated with plants.
Data from: Variable helper effects, ecological conditions, and the evolution of cooperative breeding in the acorn woodpecker
The ecological conditions leading to delayed dispersal and helping behavior are generally thought to follow one of two contrasting scenarios: that conditions are stable and predictable resulting in young being ecologically forced to remain as helpers (extrinsic constraints and the "habitat saturation" hypothesis), or that conditions are highly variable and unpredictable leading to the need for helpers to raise young, at least when conditions are poor (intrinsic constraints and the "hard life" hypothesis). We investigated how variability in ecological conditions influences the degree to which helpers augment breeder fitness in the cooperatively breeding acorn woodpecker (Melanerpes formicivorus), a species in which the acorn crop, territory quality, and prior breeding experience all vary in ways that have important effects on fitness. We found that the relationship between ecological conditions and the probability that birds would remain as helpers was variable, but that helpers generally yielded greater fitness benefits when ecological conditions were favorable, rather than unfavorable, for breeding. These results affirm the importance of extrinsic constraints to delayed dispersal and cooperative breeding in this species, despite this species' dependence on a highly variable and unpredictable acorn crop. Our findings also confirm that helpers can have very different fitness effects depending on conditions, but that those effects are not necessarily greater when breeding conditions are unfavorable.
Code and data from: Evolution of sexual cooperation from sexual conflict
<p>This C code conducts deterministic iterations of the exact recursion equations presented in the Model section of "Evolution of sexual cooperation from sexual conflict" by Servedio, Powers, Lande and Price. The code produces a two-dimensional grid with any parameters of choice on the x and y axis. Examples can be found in Figures 2c, 3c and 4 of the main text as well as many similar figures in the Supplementary Material. A sample parameter file is included as well. </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.