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108 results for “quantitative effectiveness”
Quantitative comparison of camera technologies for cost-effective Super-resolution Optical Fluctuation Imaging (SOFI) [raw datasets]
<p>Raw datasets accompanying the analysis in "Quantitative comparison of camera technologies for cost-effective Super-resolution Optical Fluctuation Imaging (SOFI)"</p> <p>The datasets contain raw fluorescence microscopy images aimed to be processed in a SOFI analysis. They are acquired with different camera technologies, allowing for direct comparison of an industry-grade CMOS detector with both a scientific-grade sCMOS and emCCD detector.</p>
Data for article: A quantitative framework to infer the effect of traits, diversity and environment on dispersal and extinction rates from fossils
<p>Supplementary information for:</p> <p><strong>A quantitative framework to infer the effect of traits, diversity and environment on dispersal and extinction rates from fossils</strong></p> <p>Torsten Hauffe, Mathias M. Pires, Tiago B. Quental, Thomas Wilke, and Daniele Silvestro</p> <p> </p><ul> <li> Simulations <ul> <li>Scripts <ul> <li>Scenario1_SamplingHeterogeneity.R: Script to simulate biogeographic histories with sampling heterogeneity</li> <li>Scenario3_SealevelInvasion.R: Script to simulate biogeographic histories where sea level facilitates dispersal and invasion induces extinction</li> <li>Scenario3_DiversityDependence.R: Script to simulate diversity-dependent biogeographic histories</li> <li>Scenario4_TraitDependence.R: Script to simulate trait-dependent biogeographic histories</li> <li>Scenario5_CategoricalTraitDependence.R: Script to simulate trait-dependent biogeographic histories</li> </ul> </li> <li>Results <ul> <li>Scenario1_SamplingHeterogenetiy_alpha05.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 0.5</li> <li>Scenario1_SamplingHeterogenetiy_alpha1.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 1</li> <li>Scenario1_SamplingHeterogenetiy_alpha2.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 2</li> <li>Scenario1_SamplingHeterogenetiy_alpha10.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 10</li> <li>Scenario2_Independent_dispersal_and_extinction.txt: Results of simulation scenario 2 with sea-level independent dispersal and no invasion induced extinction</li> <li>Scenario2_Sealevel_dependent_dispersal_and_independent_extinction.txt: Results of simulation scenario 2 with sea-level dependent dispersal and no invasion induced extinction</li> <li>Scenario2_Sealevel_independent_dispersal_and_invasion_induced_extinction.txt: Results of simulation scenario 2 with sea-level independent dispersal and invasion induced extinction</li> <li>Scenario2_Sealevel_dependent_dispersal_and_invasion_induced_extinction.txt: Results of simulation scenario 2 with sea-level dependent dispersal and invasion induced extinction</li> <li>Scenario3_Independent_dispersal_and_extinction.txt: Results of simulations scenario 3 with diversity-independent dispersal and extinction</li> <li>Scenario3_Diversity_dependent_dispersal_and_independent_extinction.txt: Results of simulations scenario 3 with diversity-dependent dispersal and diversity-independent extinction</li> <li>Scenario3_Independent_dispersal_and_Diversity_dependent_extinction.txt: Results of simulations scenario 3 with diversity-dependent dispersal and diversity-independent extinction</li> <li>Scenario3_Diversity_dependent_dispersal_and_extinction.txt: Results of simulations scenario 3 with diversity-dependent dispersal and extinction</li> <li>Scenario4_Independent_dispersal_and_extinction.txt: Results of scenario 4 with trait-independent dispersal and extinction</li> <li>Scenario4_Trait_dependent_dispersal_and_independent_extinction.txt: Results of scenario 4 with trait-dependent dispersal and independent extinction</li> <li>Scenario4_Independent_dispersal_and_trait_dependent_extinction.txt: Results of scenario 4 with independent dispersal and trait-dependent extinction</li> <li>Scenario4_trait_dependent_dispersal_and_extinction.txt: Results of scenario 4 with trait-dependent dispersal and extinction</li> <li>Scenario5_CatTrait_dependent_dispersal_and_independent_extinction.txt: Results of model 2 with categorical traits (e.g family) influence dispersal but no influence of a category-specific continuous traits</li> </ul> </li> </ul> </li> <li>Carnivora <ul> <li>BinnedOccurrence: Folder with 100 replicates of binned occurrences of max. 330 carnivoran genera throughout the Neogene</li> <li>BodyMass: Folder with 100 replicates of body mass for 330 carnivoran genera</li> <li>Sealevel: Folder with sea level through the Neogene</li> <li>Temperature: Folder with the temperature record of the Neogene</li> <li>Families: Folder with families as taxonomic proxy for phylogeny. FamilyGeneraNumeric.txt is the numeric coding used for the Bayesian analyses of carnivoran biogeography</li> </ul> </li> </ul> <p></p>
Data and code accompanying: A quantitative synthesis of and predictive framework for studying winter warming effects in reptiles
<p>This data and code were used to generate the publication "A quantitative synthesis of and predictive framework for studying winter warming effects in reptiles", doi: 10.1007/s00442-022-05251-3</p> <p>Please direct any queries or requests to use these datasets/code to: k.macleod@bangor.ac.uk</p> <p>Two datasets are presented in separate excel files: one contains meta-analytical data from experimental studies on winter warming effects on reptiles, and the other contains the same type of data from observational studies on the same.</p> <p>R code for analysis is in an R file; this should be openable in any text editing application.</p> <p>Manuscript abstract below:</p> <p><em>Increases in temperature related to global warming have important implications for organismal fitness. For ectotherms inhabiting temperate regions, ‘winter warming’ is likely to be a key source of the thermal variation experienced in future years. Studies focusing on the active season predict largely positive responses to warming in the reptiles; however, overlooking potentially deleterious consequences of warming during the inactive season could lead to biased assessments of climate change vulnerability. Here, we review the overwinter ecology of reptiles, and test specific predictions about the effects of warming winters, by performing a meta-analysis of all studies testing winter warming effects on reptile traits to date. We collated information from observational studies measuring responses to natural variation in temperature in more than one winter season, and experimental studies which manipulated ambient temperature during the winter season. Available evidence supports that most reptiles will advance phenologies with rising winter temperatures, which could positively affect fitness by prolonging the active season although effects of these shifts are poorly understood. Conversely, evidence for shifts in survivorship and body condition in response to warming winters was equivocal, with disruptions to biological rhythms potentially leading to unforeseen fitness ramifications. Our results suggest that the effects of warming winters on reptile species are likely to be important but highlight the need for more data and greater integration of experimental and observational approaches. To improve future understanding, we recap major knowledge gaps in the published literature of winter warming effects in reptiles and outline a framework for future research.</em></p>
A quantitative interphase model for polymer nanocomposites: Verification, validation, and consequences regarding size effects: dataset
<p><strong>Abstract:</strong><br> (from [1])</p> <blockquote> <p>The enhanced mechanical behavior of polymer nanocomposites with spherical filler particles is attributed to the formation of matrix-filler interphases. The nano-scale leads to particularly high interphase volume fractions while rendering experimental investigations extremely difficult. Previously, we introduced a molecular dynamics-based interphase model capturing the crucial spatial profiles of elastic and inelastic properties inside the interphase. This contribution demonstrates that our model captures polymer nanocomposites’ essential characteristics reported from experiments. To this end, we thoroughly verify and validate the model before discussing the resulting local plastic strain distribution. Furthermore, we obtain a reinforcement in terms of the overall stiffness for smaller particles and higher filler contents, while the influence of particle spacing seems negligible, matching experimental observations in the literature. This paper proposes a methodology to unravel the underlying complex mechanical behavior of polymer nanocomposites and to translate the findings into engineering quantities accessible to a broader audience and technical applications.</p> </blockquote> <p><br> <br> <strong>Contact:</strong><br> Maximilian Ries<br> Institute of Applied Mechanics<br> Friedrich-Alexander-Universität Erlangen-Nürnberg<br> Egerlandstr. 5<br> 91058 Erlangen</p> <p><strong>Software:</strong><br> Abaqus version R2018</p> <p><strong>License:</strong><br> Creative Commons Attribution 4.0 International<br> <br> <strong>Context:</strong><br> Data set supplementing journal paper:<br> [1] Ries, M.; Weber, F.; Possart, G.; Steinmann, P. & Pfaller, S., “A quantitative interphase model for polymer nanocomposites: Verification, validation, and consequences regarding size effects”, Composites Part A: Applied Science and Manufacturing, 2022, 107094.<br> This dataset contains the results presented in [1] and the necessary data to obtain those.</p> <p><br> <strong>Content:</strong></p> <p>simulation folder denotation (“-” used instead of decimal points):<br> distance_particles _ radius_particle _ thickness_ip _ num_ip _ length_box _ factor_el_length _ fraction_box_length _ switch_mat_ip</p> <p>with</p> <ul> <li> distance_particles: center distance of the nanoparticles in nm</li> <li> radius_particle: radius of the nanoparticles in nm</li> <li> thickness_ip: thickness of the interphase layers in nm</li> <li> num_ip: number of interphase layers</li> <li> length_box: box edge length in nm</li> <li> factor_el_length: factor scaling the element length on the arcs of the interphase layers (element length = factor_el_length * thickness_ip)</li> <li> fraction_box_length: matrix element length = length_box / fraction_box_length</li> <li> switch_mat_ip: if = 0: interphases are assigned their actual material properties, if = 1: interphases are assigned the material properties of the bulk</li> </ul> <p> <br> <br> each simulation folder contains the following file types:</p> <ul> <li> .cae: Abaqus model database, containing parts, meshes, loads, etc.</li> <li> .dat: Printed output from the analysis input file processor, as well as printed output of selected results written during the analysis</li> <li> .inp: Analysis input file</li> <li> .log: Log file, which contains start and end times for modules run by the current execution procedure</li> <li> .msg: Diagnostic or informative messages about the progress of the solution</li> <li> .odb: Output database containing all results data from an Abaqus analysis</li> <li> .sta: Status file with increment summaries</li> </ul> <p><strong>folder structure:</strong></p> <ul> <li>Standard_case:<br> simulation folders of the standard close (particle center distance: 5.1776 nm) and distant (particle center distance: 7.9481 nm) cases (particle radius: 2 nm, filler content 0.054 vol.%, number of interphase layers: 4, factor_el_length: 1.0) and further particle center distances</li> <li>Layers:<br> simulation folders with different numbers of interphase layers, i.e., different values for num_ip, based on the standard close and distant cases <ul> <li>Close_case</li> <li>Distant_case</li> </ul> </li> <li>Mesh:<br> simulation folders with different mesh qualities, i.e., different values for factor_el_length, based on the standard close and distant cases <ul> <li>Close_case</li> <li>Distant_case</li> </ul> </li> <li>Particle_size:<br> simulation folders with different particle sizes <ul> <li>2_nm: simulation folders with particle surface distance 2 nm <ul> <li>vol_ratio_0-00054: simulation folders with filler content 0.054 vol.%</li> <li>vol_ratio_0-0075: simulation folders with filler content 0.75 vol.%</li> </ul> </li> <li>4_nm: simulation folders with particle surface distance 4 nm <ul> <li>vol_ratio_0-00054: simulation folders with filler content 0.054 vol.%</li> <li>vol_ratio_0-0075: simulation folders with filler content 0.75 vol.%</li> </ul> </li> <li>8_nm: simulation folders with particle surface distance 8 nm <ul> <li>vol_ratio_0-00054: simulation folders with filler content 0.054 vol.%</li> <li>vol_ratio_0-0075: simulation folders with filler content 0.75 vol.%</li> </ul> </li> </ul> </li> </ul>
The effect of numerical aperture on quantitative use-wear studies and its implication on reproducibility [complement to Supplementary Material 3]
<p>Raw data, and RStudio project, R markdown scripts and HTML outputs of the statistical procedures.</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p>
Data for the article "Quantitative comparison of spin and orbital Hall and Rashba-Edelstein effects in heavy-metal/3d-metal bilayers"
<p>Data for the article "Quantitative comparison of spin and orbital Hall and Rashba-Edelstein effects in heavy-metal/3d-metal bilayers" (<a href="https://arxiv.org/abs/2004.11942">[2004.11942] Quantitative comparison of spin and orbital Hall and Rashba-Edelstein effects in heavy-metal/3d-metal bilayers (arxiv.org)</a>)</p>
A quantitative synthesis of soil microbial effects on plant species coexistence: code and data
<p>This release contains data and code to conduct all analyses in Yan et al. "A quantitative synthesis of soil microbial effects on plant species coexistence".</p>
The effect of numerical aperture on quantitative use-wear studies and its implication on reproducibility [complement to Supplementary Material 2]
<p>3D micro surface data processed in ConfoMap v7.4.8633 (a derivative of MountainsMap Imaging Topography developed by Digital Surf, Besançon, France).</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p>
The effect of numerical aperture on quantitative use-wear studies and its implication on reproducibility [complement to Supplementary Material 4]
<p>Python script and results of the Bayesian Multi-factor ANOVA.</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p>
Table 2. Studies on psychiatric side effects of fluoroquinolones. The risk of bias and study quality assessed with the Effective Public Health Practice Project's Quality Assessment Tool for Quantitative Studies (QATQS) was presented as the global rating for each publication (3 – weak).
<p>Studies on psychiatric side effects of fluoroquinolones. The risk of bias and study quality assessed with the Effective Public Health Practice Project’s Quality Assessment Tool for Quantitative Studies (QATQS) was presented as the global rating for each publication (3 – weak).</p>
Data from: Large effect quantitative trait loci for salicinoid phenolic glycosides in Populus: implications for gene discovery
Open the record for dataset details and reuse information.
Data from: the quantitative genetic basis of variation in sexual versus non-sexual butterfly wing colouration: autosomal, Z-linked and maternal effects
Open the record for dataset details and reuse information.
Data from: Quantitative genetics of a carotenoid-based color: heritability and persistent natal environmental effects in the great tit
The information content of signals, such as animal coloration, depends on the extent to which variation reflects underlying biological processes. Although animal coloration has received considerable attention, little work has addressed the quantitative genetics of colour variation in natural populations. We investigated the quantitative genetics of a carotenoid-based colour patch - the ventral plumage of mature great tits (Parus major) - in a wild population. Carotenoid-based colours are often suggested to reflect environmental variation in carotenoid availability, but numerous mechanisms could also lead to genetic variation in coloration. Analyses of individuals of known origin showed that while plumage chromaticity ('colour') was moderately heritable, there was no significant heritability to achromaticity ('brightness'). We detected multiple long-lasting effects of natal environment, with hatching date and brood size both negatively related to plumage chromaticity at maturity. Our reflectance measures contrasted in their spatiotemporal sensitivity, with plumage chromaticity exhibiting significant spatial variation while achromatic variation exhibited marked annual variation. Hence, colour variation in this species reflects both genetic and environmental influences on different scales. Our analyses demonstrate the context-dependence of components of colour variation and suggest that colour patches may convey multiple aspects of individual state.
Data from: Widespread cumulative influence of small effect size mutations on yeast quantitative traits
Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect-size genes could cumulatively play a substantial role in pathway function. Here, we determined the number, strength and identity of all non-essential test genes that affect two quantitative galactose-responsive traits, in addition to re-analyzing two previously screened quantitative traits. We find that over a quarter of assayed genes have a detectable, quantitative effect on phenotype. Despite their ubiquity, these genes are enriched in core cellular processes in a trait-specific manner. In a simulated population with 50% frequency of all-or-none alleles, we show that small effect-size alleles are capable of contributing more to trait variation than alleles in a canonical, large-effect size pathway. In total, by demonstrating that the genes effecting quantitative traits can be highly distributed and interconnected, this work challenges the concept of pathways as modular and independent.
Data from: Assessing the effects of quantitative host resistance on the life-history traits of sporulating parasites with growing lesions
Assessing life-history traits of parasites on resistant hosts is crucial in evolutionary ecology. In the particular case of sporulating pathogens with growing lesions, phenotyping is difficult because one needs to disentangle properly pathogen spread from sporulation. By considering Phytophthora infestans on potato, we use mathematical modelling to tackle this issue and refine the assessment pathogen response to quantitative host resistance. We elaborate a parsimonious leaf-scale model by convolving a lesion growth model and a sporulation function, after a latency period. This model is fitted to data obtained on two isolates inoculated on three cultivars with contrasted resistance level. Our results confirm a significant host-pathogen interaction on the various estimated traits, and a reduction of both pathogen spread and spore production, induced by host resistance. Most interestingly, we highlight that quantitative resistance also changes the sporulation function, whose mode is significantly time-lagged.This alteration of the infectious period distribution on resistant hosts may have strong impacts on the dynamics of parasite populations, and should be considered when assessing the durability of disease control tactics based on plant resistance management. This inter-disciplinary work also supports the relevance of mechanistic models for analysing phenotypic data of plant-pathogen interactions.
Data from: Quantitative genetics of plumage color: lifetime effects of early nest environment on a colorful sexual signal
Phenotypic differences among individuals are often linked to differential survival and mating success. Quantifying the relative influence of genetic and environmental variation on phenotype allows evolutionary biologists to make predictions about the potential for a given trait to respond to selection and various aspects of environmental variation. In particular, the environment individuals experience during early development can have lasting effects on phenotype later in life. Here, we used a natural full-sib/half-sib design as well as within-individual longitudinal analyses to examine genetic and various environmental influences on plumage color. We find that variation in melanin-based plumage color – a trait known to influence mating success in adult North American barn swallows (Hirundo rustica erythrogaster) – is influenced by both genetics and aspects of the developmental environment, including variation due to the maternal phenotype and the nest environment. Within individuals, nestling color is predictive of adult color. Accordingly, these early environmental influences are relevant to the sexually selected plumage color variation in adults. Early environmental conditions appear to have important lifelong implications for individual reproductive performance through sexual signal development in barn swallows. Our results indicate that feather color variation conveys information about developmental conditions and maternal care alleles to potential mates in North American barn swallows. Melanin-based colors are used for sexual signaling in many organisms, and our study suggests that these signals may be more sensitive to environmental variation than previously thought.
Data from: The effects of quantitative fecundity in the haploid stage on reproductive success and diploid fitness in the aquatic peat moss Sphagnum macrophyllum
A major question in evolutionary biology is how mating patterns affect the fitness of offspring. However, in animals and seed plants it is virtually impossible to investigate the effects of specific gamete genotypes. In bryophytes, haploid gametophytes grow via clonal propagation and produce millions of genetically identical gametes throughout a population. The main goal of this research was to test whether gamete identity has an effect on the fitness of their diploid offspring in a population of the aquatic peat moss Sphagnum macrophyllum. We observed a heavily male-biased sex ratio in gametophyte plants (ramets) and in multilocus microsatellite genotypes (genets). There was a steeper relationship between mating success (number of different haploid mates) and fecundity (number of diploid offspring) for male genets compared with female genets. At the sporophyte level, we observed a weak effect of inbreeding on offspring fitness, but no effect of brood size (number of sporophytes per maternal ramet). Instead, the identities of the haploid male and haploid female parents were significant contributors to variance in fitness of sporophyte offspring in the population. Our results suggest that intrasexual gametophyte/gamete competition may play a role in determining mating success in this population.
Global quantitative synthesis of effects of biotic and abiotic factors on stemflow production in woody ecosystems
<p><span><b>Aim: </b>Stemflow has been increasingly recognized as an indispensable component in water and nutrient budgets within vegetated ecosystems. Here we aim to quantify the stemflow percentage (St, %) of incident precipitation (i.e., stemflow production) at a global scale, and to provide a systematic evaluation on how biotic and abiotic factors affect St.</span></p> <p><span><b>Location: </b>Global</span></p> <p><span><b>Time period: </b>1970 – 2019</span></p> <p><span><b>Major taxa studied: </b>Woody plants (trees and shrubs)</span></p> <p><span><b>Methods: </b>We compiled a global stemflow dataset from 234 peer-reviewed papers, which included 488 observations of St and the related biotic (stand characteristics) and abiotic factors (climate variables) at 283 sites within terrestrial woody plant ecosystems. We explored the global pattern of St and performed a machine learning method (boosted regression trees) to model the effects of biotic and abiotic variables on St.</span></p> <p><span><b>Results: </b>Globally, the median (interquartile range, IQR) St was 2.7 % (1.0 – 6.3 %). We found that St in arid zones (type B in Köppen-Geiger climate classification) was significant higher (<i>P</i> < 0.01) than in other climate types, and we also detected a significant difference (<i>P</i> < 0.01) in St between trees (median: 2.4 %; IQR: 1.0 – 5.3 %) and shrubs (median: 7.2 %; IQR: 5.2 – 11.9 %). Predictor variables that substantially accounted for the explained deviance of the final model included vegetation height (27.0 %), mean annual precipitation (16.1 %), mean annual temperature (14.4 %), stand density (10.8 %), stand age (8.9 %), and bark type (5.5 %). In contrast, leaf area index, diameter at breast height, basal area, phenology type, life form, and leaf type were classified as low importance.</span></p> <p><span><b>Main conclusions: </b>Our synthesis provides a cross-site comparison of St, and gives a holistic view on how climate variables and stand characteristics contribute to and affect global stemflow production.</span></p>
Causal effect of familial short stature on three quantitative traits in Taiwan
<p><span><strong>Objectives</strong>: </span><span>With the accumulation of genetic basis for </span><span>familial (genetic) short stature (FSS)</span><span>, the genetic association of FSS with health-related outcomes remains to be elucidated. In this study, we aimed to investigate the FSS genetic architecture and its causal effect on three quantitative traits in Taiwan. </span></p> <p><span><strong>Methods</strong>:</span><span> We </span><span>conducted an FSS genome-wide association study (GWAS) analysis (1,640 FSS cases and 22,372 controls). We performed a GWAS meta-analysis for the Taiwanese meta-height from the Taiwan Biobank (</span><span>TWB)_height (N = 67,452) and the China Medical University Hospital (CMUH)_height GWAS summary statistics (N = 88,854). </span><span>We calculated three polygenic risk scores (PRSs) of SNPs (<em>P</em> < 5 x 10<sup>-8</sup>) for FSS and Taiwanese meta-height with/without FSS, respectively. We explored the associations between three PRSs and the measured height, respectively. We also performed </span><span>Mendelian randomization (MR) analysis</span><span> for the causal effect of FSS and Taiwanese meta-height with/without FSS, on anthropometric, bone mineral density (BMD), and female reproductive traits</span><span>. </span></p> <p><span><strong>Results</strong>: </span><span>FSS GWAS identified 172 SNPs in 4 genomic regions, reported in height </span><span>(<em>P</em> < 5 x 10<sup>-8</sup>)</span><span>. Higher FSS genetic scores correlate with an increased risk of short stature and height reduction tendency </span><span>(</span><em><span>p</span></em> <span><</span><span> 0.001).</span><span> The causal effect showed that a higher risk of FSS was associated with decreased body height, but increased body mass index, and body fat</span> <span>(</span><em><span>p</span></em> <span><</span><span> 0.001)</span><span>. However, higher genetic scores of Taiwanese meta-height with/without FSS correspond with increased body height, body weight, hip circumference, and age at menarche, but decreased BMD_T-score, BMD_Z-score, and stiffness index </span><span>(</span><em><span>p</span></em> <span><</span><span> 0.001)</span><span>. </span></p> <p><span><strong>Conclusion</strong>: </span><span>This study </span><span>contributes to the FSS and height genetic features and their causal effects on three quantitative traits </span><span>in individuals of Han Chinese ancestry in Taiwan. </span></p>
Quantitative effects data example (qData_v3.5.xlsx)
<p>Example of dose-response data set from different species, stressors, endpoints. The data set contains data and metadata used to quantitate the dose (concentration) response (effect) relationships for different stressors. The xlsx workbook contain the following sheets:</p> <p>Introduction: Brief explanation to the qData template and example data set included</p> <p>README: The README file provides an overview of the basic features of the qData template. The sheet contains overview of all columns in the qData template (and example), explanation to column title in the template and web-based user interface (UI), description for the column content, Format of data, examples, Schemas used for the UI and identification of specific lookuptables used to parametrise the data in the clumn. </p> <p>qData: the sheet contain the data and metadata for chemicals (2,5-dicholorophenol, diuron, cadmium), UV-B and gamma radiation. Test species include Daphnia magna, Lemna minor, Chlamydomonas reinhardtii and Tisbe battagliai. The README file and the notes to column titles provide explanation to content of the cells</p> <p>*_LOOKUP: a number of lookup tables to provide values to the qdata template/example. This is used for adding data, not to use data.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.