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157 results for “Evolutionary Studies”
Data Sets for the study "What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms"
<p>This is the dataset of the paper "What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms"</p> <ul> <li>figures.ipynb provides postprocessing codes for using the attached data to generate tables and figures in the paper.</li> <li>the csv folder consists of the raw data of function evaluations that algorithms used to hit each solution the first time.</li> <li>the metric folder consists of the processed data, which records the convergence process of two single objectives (y1 and y2), Hypervolume, and the number of obtained Pareto solutions.</li> <li>the gif folder consists of the gif files plotting the convergence process of solving LOTZ.</li> </ul> <p> </p> <p>The code used to generate this data is available at https://github.com/FurongYe/GSEMO</p>
Data from: Using time series analysis to characterize evolutionary and plastic responses to environmental change: a case study of a shift toward earlier migration date in sockeye salmon
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Data from: Evolutionary history as a driver of ecological networks: a case study of plant-hummingbird interactions
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Data from: Mosaic heterochrony and evolutionary modularity: the trilobite genus Zacanthopsis as a case study
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Data from: Is the switch to an ectomycorrhizal state an evolutionary key innovation in mushroom-forming fungi? a case study in the tricholomatineae (agaricales)
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Data from: Application of CRISPR/Cas9 to Tragopogon (Asteraceae), an evolutionary model for the study of polyploidy
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The evolutionary dynamics of plant mating systems: how bias for studying ‘interesting’ plant reproductive systems could backfire
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Data from: First plastid phylogenomic study reveals potential cyto-nuclear discordance in the evolutionary history of Ficus L. (Moraceae)
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Data from: The role of hybridisation in the origin and evolutionary persistence of vertebrate parthenogens: a case study of Darevskia lizards
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Analyzing evolutionary game theory in epidemic management: A study on social distancing and mask-wearing strategies
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Data from: Evolutionary history of a beautiful damselfly, Matrona basilaris, revealed by phylogeographic analyses: the first study of an odonate species in mainland China
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A multi-tiered sequence capture strategy spanning broad evolutionary scales: application for phylogenetic and phylogeographic studies of orchids
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Understanding the Early Evolutionary Stages of a Tandem Drosophila melanogaster - Specific Gene Family: A Structural and Functional Population Study
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Figure 2 from: Sabino Kikuchi IAB, Keβler PJA, Schuiteman A, Murata J, Ohi-Toma T, Yukawa T, Tsukaya H (2020) Molecular phylogenetic study of the tribe Tropidieae (Orchidaceae, Epidendroideae) with taxonomic and evolutionary implications. PhytoKeys 140: 11-22. https://doi.org/10.3897/phytokeys.140.46842
Figure 2 Phylogenetic relationships of Tropidieae based on Maximum Likelihood analysis on three non-plastid regions (ITS, nad1 b-c intron and Xdh). Numbers at nodes are Bootstrap Percentages obtained by Maximum Likelihood analysis and Bayesian Posterior Probabilities, respectively. Fully mycoheterotrophic species are shown in bold. Red branches indicate mycoheterotrophic origins. The scale bar below the tree indicates the substitution rate.
Figure 1 from: Sabino Kikuchi IAB, Keβler PJA, Schuiteman A, Murata J, Ohi-Toma T, Yukawa T, Tsukaya H (2020) Molecular phylogenetic study of the tribe Tropidieae (Orchidaceae, Epidendroideae) with taxonomic and evolutionary implications. PhytoKeys 140: 11-22. https://doi.org/10.3897/phytokeys.140.46842
Figure 1 Tropidia connata J.J.Wood & A.L.Lamb and Kalimantanorchis nagamasui Tsukaya, M.Nakaj. & H.Okada. A Gross morphology of T. connata individual (specimen number 1040, collected in January, 2011 by H. Tsukaya, H. Okada and A. Soejima). B Gross morphology of fruiting K. nagamasui individual (specimen number HT1035, collected in January, 2011 by H. Tsukaya, H. Okada and A. Soejima). Scale in cm.
Data from: Toward synthesizing our knowledge of morphology: using ontologies and machine reasoning to extract presence/absence evolutionary phenotypes across studies
The reality of larger and larger molecular databases and the need to integrate data scalably have presented a major challenge for the use of phenotypic data. Morphology is currently primarily described in discrete publications, entrenched in noncomputer readable text, and requires enormous investments of time and resources to integrate across large numbers of taxa and studies. Here we present a new methodology, using ontology-based reasoning systems working with the Phenoscape Knowledgebase (KB; kb.phenoscape.org), to automatically integrate large amounts of evolutionary character state descriptions into a synthetic character matrix of neomorphic (presence/absence) data. Using the KB, which includes more than 55 studies of sarcopterygian taxa, we generated a synthetic supermatrix of 639 variable characters scored for 1051 taxa, resulting in over 145,000 populated cells. Of these characters, over 76% were made variable through the addition of inferred presence/absence states derived by machine reasoning over the formal semantics of the source ontologies. Inferred data reduced the missing data in the variable character-subset from 98.5% to 78.2%. Machine reasoning also enables the isolation of conflicts in the data, that is, cells where both presence and absence are indicated; reports regarding conflicting data provenance can be generated automatically. Further, reasoning enables quantification and new visualizations of the data, here for example, allowing identification of character space that has been undersampled across the fin-to-limb transition. The approach and methods demonstrated here to compute synthetic presence/absence supermatrices are applicable to any taxonomic and phenotypic slice across the tree of life, providing the data are semantically annotated. Because such data can also be linked to model organism genetics through computational scoring of phenotypic similarity, they open a rich set of future research questions into phenotype-to-genome relationships.
Data from: How scientists perceive the evolutionary origin of human traits: results of a survey study
Various hypotheses have been proposed for why the traits distinguishing humans from other primates originally evolved, and any given trait may have been explained both as an adaptation to different environments and as a result of demands from social organization or sexual selection. To find out how popular the different explanations are among scientists, we carried out an online survey among authors of recent scientific papers in journals covering relevant fields of science (palaeoanthropology, palaeontology, ecology, evolution, human biology). Some of the hypotheses were clearly more popular among the 1266 respondents than others, but none was universally accepted or rejected. Even the most popular of the hypotheses were assessed "very likely" by <50 % of the respondents, but many traits had 1–3 hypotheses that were found at least moderately likely by >70 % of the respondents. An ordination of the hypotheses identified two strong gradients. Along one gradient, the hypotheses were sorted by their popularity, measured by the average credibility score given by the respondents. The second gradient separated all hypotheses postulating adaptation to swimming or diving into their own group. The average credibility scores given for different subgroups of the hypotheses were not related to respondent's age or number of publications authored. However, (palaeo)anthropologists were more critical of all hypotheses, and much more critical of the water-related ones, than were respondents representing other fields of expertise. Although most respondents did not find the water-related hypotheses likely, only a small minority found them unscientific. The most popular hypotheses were based on inherent drivers, i.e. they assumed the evolution of a trait to have been triggered by the prior emergence of another human-specific behavioural or morphological trait, but opinions differed as to which of the traits came first.
Data from: Interpreting the evolutionary regression: the interplay between observational and biological errors in phylogenetic comparative studies
Regressions of biological variables across species are rarely perfect. Usually there are residual deviations from the estimated model relationship, and such deviations commonly show a pattern of phylogenetic correlations indicating that they have biological causes. We discuss the origins and effects of phylogenetically correlated biological variation in regression studies. In particular, we discuss the interplay of biological deviations with deviations due to observational or measurement errors, which are also important in comparative studies based on estimated species means. We show how bias in estimated evolutionary regressions can arise from several sources, including phylogenetic inertia and either observational or biological error in the predictor variables. We show how all these biases can be estimated and corrected for in the presence of phylogenetic correlations. We present general formulas for incorporating measurement error in linear models with correlated data. We also show how alternative regression models, such as major-axis and reduced major-axis regression, which are often recommended when there is error in predictor variables, are strongly biased when there is biological variation in any part of the model. We argue that such methods should never be used to estimate evolutionary or allometric regression slopes.
Data from: A population study of killer viruses reveals different evolutionary histories of two closely related Saccharomyces sensu stricto yeasts
Microbes have evolved ways of interference competition to gain advantage over their ecological competitors. The use of secreted killer toxins by yeast cells through acquiring double-stranded RNA viruses is one such prominent example. Although the killer behaviour has been well studied in laboratory yeast strains, our knowledge regarding how killer viruses are spread and maintained in nature and how yeast cells co-evolve with viruses remains limited. We investigated these issues using a panel of 81 yeast populations belonging to three Saccharomyces sensu stricto species isolated from diverse ecological niches and geographic locations. We found that killer strains are rare among all three species. In contrast, killer toxin resistance is widespread in Saccharomyces paradoxus populations, but not in Saccharomyces cerevisiae or Saccharomyces eubayanus populations. Genetic analyses revealed that toxin resistance in S. paradoxus is often caused by dominant alleles that have independently evolved in different populations. Molecular typing identified one M28 and two types of M1 killer viruses in those killer strains. We further showed that killer viruses of the same type could lead to distinct killer phenotypes under different host backgrounds, suggesting co-evolution between the viruses and hosts in different populations. Taken together, our data suggest that killer viruses vary in their evolutionary histories even within closely related yeast species.
Data from: Target capture and massively parallel sequencing of ultraconserved elements for comparative studies at shallow evolutionary time scales
Comparative genetic studies of non-model organisms are transforming rapidly due to major advances in sequencing technology. A limiting factor in these studies has been the identification and screening of orthologous loci across an evolutionarily distant set of taxa. Here, we evaluate the efficacy of genomic markers targeting ultraconserved DNA elements (UCEs) for analyses at shallow evolutionary timescales. Using sequence capture and massively parallel sequencing to generate UCE data for five co-distributed Neotropical rainforest bird species, we recovered 776–1516 UCE loci across the five species. Across species, 53–77% of the loci were polymorphic, containing between 2.0 and 3.2 variable sites per polymorphic locus, on average. We performed species tree construction, coalescent modeling, and species delimitation, and we found that the five co-distributed species exhibited discordant phylogeographic histories. We also found that species trees and divergence times estimated from UCEs were similar to the parameters obtained from mtDNA. The species that inhabit the understory had older divergence times across barriers, contained a higher number of cryptic species, and exhibited larger effective population sizes relative to the species inhabiting the canopy. Because orthologous UCEs can be obtained from a wide array of taxa, are polymorphic at shallow evolutionary timescales, and can be generated rapidly at low cost, they are an effective genetic marker for studies investigating evolutionary patterns and processes at shallow timescales.
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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.