Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,092
datasets available to search
ShareScore release 0.9.0
Dataset results
1,092 results for “quantifiers”
Quantifying the Tissue-Specific Regulatory Information within Enhancer DNA Sequences
<p>Tables of mouse embryonic differential enhancers and promoters.</p> <p>The tables list the genomic coordinates of differential regulatory elements, the tissues in which they are active (labels column), a differential score, and the DNA sequence of the element. Tissues are numbered from 0 to 7, which correspond to heart, kidney, liver, limb, lung, forebrain, midbrain, and hindbrain, respectively. The tool <a href="https://github.com/pbenner/gonetics/tree/master/tools/segmentationDifferential">segmentationDifferential</a> from the <em>gonetics library</em> was used to compute differential elements. The length of all regions was set to 1000 base pairs around the center. Specifics of the experimental data can be found in the referenced publication.</p>
Quantifying Hierarchy and Prestige in US Ballet Academies as Social Predictors of Career Success
<p>This data contains aggregated competition outcomes from 6,363 ballet students affiliated with 1,603 schools in the United States, who participated in the Youth America Grand Prix (YAGP) between 2000 and 2021.</p> <p>We adopt a network science and <em>science of science</em> approach that empowers logistic regression models and matching experiments to quantify social prestige and its influence on dancers' careers. The analysis of career success in the performing arts, like ballet, in the context of a competition setting offers a unique opportunity to investigate the social influences on success while controlling for competition performance.</p> <p>Our work reveals the importance of institutional prestige on career success in ballet and showcases the potential of network science approaches to provide quantitative viewpoints for the professional development of careers beyond science.</p>
Original data for "Imaging and quantifying the chemical communication between single particles in metal alloy" article
<p>This upload contains original data and supplementary data for the publication titled "Imaging and Quantifying the Chemical Communication Between Single Particles in Metal Alloy" by L. Godeffroy, A. Makogon, S. G. Derouich, F. Kanoufi, V. Shkirskiy in the ACS Analytical Chemistry journal. The preprint of the paper is included in this upload and is also available on ChemRxiv (<a href="https://doi.org/10.26434/chemrxiv-2022-rn77b-v2">https://doi.org/10.26434/chemrxiv-2022-rn77b-v2</a>). </p> <p>The file "OpticalData.zip" contains the original optical images. Each pixel in the images has a size of 180 nm, and the time interval between frames is 1.87 seconds.</p> <p>The file "sem_identical.png" contains a scanning electron microscopy (SEM) image of the same surface area as the optical images, captured using secondary electrons.</p> <p>The file "WorkingWithData.ipynbb" is a Jupyter Lab file that demonstrates a few examples of how data can be loaded and processed in a Python environment. Python 3 was used for this purpose.</p> <p>There are also two supplementary movies:</p> <p>Movie S1: This movie provides an enlarged view (marked with a square in Movie S2) of the surface film transformation on Al6061 during immersion in 10 mM H2SO4. It includes snapshots at 17 s, 28 s, 37 s, and 84 s, along with a related SEM image of the same location.</p> <p>Movie S2: This movie presents a wide-field view of the surface film transformation on Al6061 during immersion in 10 mM H2SO4, along with a related SEM image of the same location. The square highlights the area around which the narrative in the manuscript is focused.</p>
Supplementary data for the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand"
<p>Binarized cutouts (black=pore, white=soil) of 3D CT images of soil samples from loam and sand together with geometrical descriptors and diffusive properties computed on these cutouts. The geometrical descriptors include, among others, porosity, specific surface area, geodesic tortuosity, geometric tortuosity, constrictivity, mean chord length and mean of spherical contact distribution. Diffusion is quantified by the so-called M-factor which equals the ratio of the effective and intrinsic diffusivity.</p> <p>This data supplements the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand". Additional information can be found there.</p>
Data and scripts for reproducing "Quantifying Uncertainties in Direct Numerical Simulations of a Turbulent Channel Flow"
<p>This is the accompanying data and Python scripts to reproduce the figures in "Quantifying Uncertainties in Direct Numerical Simulations of a Turbulent Channel Flow", currently under review.</p>
Quantifying Changes along Mainland Marshes in the Virginia Coast Reserve, 1957-2011: GIS data
This dataset contains data that quantifies the long-term rate of change in the shoreline position along seaside mainland marshes of the Virginia Coast Reserve between 1957 and 2009. It also contains data that delineates potential areas available for future marsh transgression under three different sea level rise scenarios based on current land use and elevation data. Shoreline position was determined for ten individual mainland marsh sites 3-4 km in length, plus the full length of the mainland marsh edge along the entire seaside length of the peninsula, based on aerial imagery from 1957, 1966, 1989, 2002, and 2009. The ten marsh sites (north to south) were at Gargathy Bay, Cedar Island Bay, Hummock Cove, Wachapreague, North Matulakin Marsh, Short and Long Prong Marshes, Crabbing Marsh, Oyster, Mockhorn Bay, and Marion Scott Cove. Metrics of the rate of change were determined using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension (Thieler et al., 2009). Given the digitized shorelines and a parallel baseline as inputs, DSAS creates evenly-spaced transects perpendicular to the baseline and calculates the rate of shoreline change using a variety of methods, including the End Point Rate (EPR), linear regression rate (LRR), and various iterative and weighted linear regressions. Statistics for these regressions are included in the transect and summary point attribute data. Areas potentially suitable for future marsh transgression based on land use were determined based on 2005 NOAA Coastal Change Analysis Program (CCAP) data and consisted of upland and wetland areas currently in forest or scrub/shrub cover and adjacent to existing marshes. The acreage of these potential marsh areas that could be inundated and unavailable for marsh transgression under three different sea level rise scenarios was also determined based on elevation data from 2010 LiDAR surveys (see VCRLTER dataset VCR12194). Data on sediment grain size characteristics from the field collectio
Quantifying Changes along Mainland Marshes in the Virginia Coast Reserve, 1957-2011: Tabular data
This dataset contains data that quantifies the long-term rate of change in the shoreline position along seaside mainland marshes of the Virginia Coast Reserve between 1957 and 2009. It also contains data that delineates potential areas available for future marsh transgression under three different sea level rise scenarios based on current land use and elevation data. Additionally, the tabular data contains sediment grain size analysis results from sediment cores collected in 2011 at six of the ten study sites, plus GPS elevation profiles of the marsh edges at those sites. Shoreline position was determined for ten individual mainland marsh sites 3-4 km in length, plus the full length of the mainland marsh edge along the entire seaside length of the peninsula, based on aerial imagery from 1957, 1966, 1989, 2002, and 2009. The ten marsh sites (north to south) were at Gargathy Bay, Cedar Island Bay, Hummock Cove, Wachapreague, North Matulakin Marsh, Short and Long Prong Marshes, Crabbing Marsh, Oyster, Mockhorn Bay, and Marion Scott Cove. Metrics of the rate of change were determined using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension (Thieler et al., 2009). Given the digitized shorelines and a parallel baseline as inputs, DSAS creates evenly-spaced transects perpendicular to the baseline and calculates the rate of shoreline change using a variety of methods, including the End Point Rate (EPR), linear regression rate (LRR), and various iterative and weighted linear regressions. Statistics for these regressions are included in the transect and summary point attribute data. Areas potentially suitable for future marsh transgression based on land use were determined based on 2005 NOAA Coastal Change Analysis Program (CCAP) data and consisted of upland and wetland areas currently in forest or scrub/shrub cover and adjacent to existing marshes. The acreage of these potential marsh areas that could be inundated and unavailable for marsh transgression under
Repository: Quantifying environmental impacts of primary aluminum ingot production and consumption: A trade-linked multilevel life cycle assessment
<p>This repository contains the input data, codes and results of the model developed in the paper "Quantifying environmental impacts of primary aluminum ingot production and consumption: A trade-linked multilevel life cycle assessment" published in the Journal of Industrial Ecology (2020) by Alexandre Milovanoff, I. Daniel Posen, Heather L. MacLean.</p>
Supplementary data: Quantifying and numerically representing recharge and flow components in a karstified carbonate aquifer
<p>The following data and information is related to the paper "Quantifying and numerically representing recharge and flow components in a karstified carbonate aquifer":</p> <p>Observed and estimated hydrological time series (hourly spring discharge, hourly rainfall, daily minimum and maximum air temperature and evapotranspiration) and modelling results (hourly discharges and flows) using an InfoWorks ICM pipe network model, as well as R code to compute Fourier transform / power spectrum of time series.</p> <p>See 'readme_Schuler_etal_WRR_supplementary data.pdf' for more information.</p>
Quantifying dispersal variability among nearshore marine populations
<p>Project measuring variability in larval dispersal for clownfish <em>Amphiprion clarkii</em>. This repository is organized into 3 folders:</p> <ol> <li>code -This contains the R code to produce the results in the manuscript “Quantifying dispersal variability among nearshore marine populations”. My original coding was done in Jupyter Notebooks (IR Kernel). These notebooks are included in the folder "WorkingJupyterNotebooks", and can be viewed as HTML using the web site <a href="https://nbviewer.jupyter.org/">https://nbviewer.jupyter.org/</a>. The .R files were produced by downloading these notebooks as .R files.</li> <li>data -This contains the data to run the analysis using the code. The genomic data here is a filtered to use in Colony2. It also contains a backup of the SQL database with all data for the clownfish field and wetlab work in the Pinsky lab.</li> <li>genomics -This is the version of <a href="https://github.com/pinskylab/genomics">https://github.com/pinskylab/genomics</a> as it was at the time of this project. It contains all molecular wetlab metadata, raw genomic data, bioinformatics code, and protocols.</li> </ol> <p>Please contact Katrina at <a href="mailto:kat.catalano@rutgers.edu">kat.catalano@rutgers.edu</a> with any questions.</p>
Data from: Quantifying nectar production by flowering plants in urban and rural landscapes
<p>Floral resources (nectar and pollen) provide food for insect pollinators but have declined in the countryside due to land use change. Given widespread pollinator loss, it is important that we quantify their food supply to help develop conservation actions. While nectar resources have been measured in rural landscapes, equivalent data are lacking for urban areas, an important knowledge gap as towns and cities often host diverse pollinator populations.</p> <p>We quantified the nectar supply of urban areas, farmland and nature reserves in the UK by combining floral abundance and nectar sugar production data for 536 flowering plant taxa, allowing us to compare landscape types and assess the spatial distribution of nectar sugar among land uses within cities.</p> <p>The magnitude of nectar sugar production did not differ significantly among the three landscapes. In urban areas the nectar supply was more diverse in origin and predominantly delivered by non-native flowering plants. Within cities, urban land uses varied greatly in nectar sugar production. Gardens provided the most nectar sugar per unit area and 85% of all nectar at a city scale, while gardens and allotments produced the most diverse supplies of nectar sugar. Floral abundance, commonly used as a proxy for pollinators' food supply, correlated strongly with nectar resources, but left a substantial proportion of the variation in nectar supply unexplained.</p> <p>Synthesis. We show that urban areas are hotspots of floral resource diversity rather than quantity and their nectar supply is underpinned by the contribution of residential gardens. Individual gardeners have an important role to play in pollinator conservation as ornamental plants, usually non-native in origin, are a key source of nectar in towns and cities.</p>
Data from: Multimodal in situ datalogging quantifies inter-individual variation in thermal experience and persistent origin effects on gaping behavior among intertidal mussels (Mytilus californianus)
In complex habitats, environmental variation over small spatial scales can equal or exceed larger-scale gradients. This small-scale variation may allow motile organisms to mitigate stressful conditions by choosing benign microhabitats, whereas sessile organisms may rely on other behaviors to cope with environmental stresses in these variable environments. We developed a monitoring system to track body temperature, valve gaping behavior, and posture of individual mussels (Mytilus californianus) in field conditions in the rocky intertidal zone. Neighboring mussels' body temperatures varied by up to 14°C during low tides. Valve gaping during low tide and postural adjustments, which could theoretically lower body temperature, were not commonly observed. Rather, gaping behavior followed a tidal rhythm at a warm, high intertidal site; this rhythm shifted to a circadian period at a low intertidal site and for mussels continuously submerged in a tidepool. However, individuals within a site varied considerably in time spent gaping when submerged. This behavioral variation could be attributed in part to persistent effects of mussels' developmental environment. Mussels originating from a wave-protected, warm site gaped more widely, and they remained open for longer periods during high tide than mussels from a wave-exposed, cool site. Variation in behavior was modulated further by recent wave heights and body temperatures during the preceding low tide. These large ranges in body temperatures and durations of valve closure events - which coincide with anaerobic metabolism - support the conclusion that individuals experience "homogeneous" aggregations such as mussel beds in dramatically different fashion, ultimately contributing to physiological variation among neighbors.
Dataset from "Quantifying air-sea gas exchange using noble gases in a coastal upwelling zone"
<p>Dataset of dissolved noble gas (He, Ne, Ar, Kr, and Xe) measurements in Monterey Bay, CA. Published as a supplement to: Manning, C.C., R.H.R. Stanley, D.P. Nicholson, and M.E. Squibb (2016). Quantifying air-sea gas exchange using noble gases in a coastal upwelling zone. <em>IOP Conference Series: Earth and Environmental Science</em>, 35, 012017 (13 pp). doi: 10.1088/1755-1315/35/1/012017</p>
Efficient assays to quantify the life history traits of algal viruses
<p>Data and analysis files accompanying the paper 'Efficient assays to quantify the life history traits of algal viruses' (Lievens et al. 2023, Applied & Environmental Microbiology). Includes data and code for the modified one-step growth (mOSG) assay, modified survival (mS) assay, and comparison of the two assays.</p> <p>The only difference with the previous version of this package (doi 10.5281/zenodo.6573770) is that two typos were corrected in the file "mOSG & mS comparison.rmd" (lines 172 & 182; corrections noted in the script).</p>
A computational neuroscience framework for quantifying warning signals
<p>Animal warning signals show remarkable diversity, yet subjectively appear to share certain visual features that make defended prey stand out and look different from more cryptic palatable species. For example, many (but far from all) warning signals involve high contrast elements, such as stripes and spots, and often involve the colours yellow and red. How exactly do aposematic species differ from non-aposematic ones in the eyes (and brains) of their predators?</p> <p>Here we develop a novel computational modelling approach, to quantify prey warning signals and establish what visual features they share. First, we develop a model visual system, made of artificial neurons with realistic receptive fields, to provide a quantitative estimate of the neural activity in the first stages of the visual system of a predator in response to a pattern. The system can be tailored to specific species. Second, we build a novel model that defines a 'neural signature', comprising quantitative metrics that measure the strength of stimulation of the population of neurons in response to patterns. This framework allows us to test how individual patterns stimulate the model predator visual system.</p> <p>For the predator-prey system of birds foraging on lepidopteran prey, we compared the strength of stimulation of a modelled avian visual system in response to a novel database of hyperspectral images of aposematic and undefended butterflies and moths. Warning signals generate significantly stronger activity in the model visual system, setting them apart from the patterns of undefended species. The activity was also very different from that seen in response to natural scenes. Therefore, to their predators, lepidopteran warning patterns are distinct from their non-defended counterparts, and stand out against a range of natural backgrounds.</p> <p>For the first time, we present an objective and quantitative definition of warning signals based on how the pattern generates population activity in a neural model of the brain of the receiver. This opens new perspectives for understanding and testing how warning signals have evolved, and, more generally, how sensory systems constrain signal design.</p>
Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities
<p>Dataset for publication Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities</p>
Unpublished data: Quantifying CO2 Emissions and Carbon Sequestration from Digestate-Amended Soil Using Natural 13C Abundance as a Tracer
<p>Unprocessed data of CO2 evolution measured daily on cavity ring-down spectroscopy analyser (G2201-i CRDS isotopic CO2/CH4 analyser, Picarro, Santa Clara, CA, USA).</p>
Artifact of 'Unification for Subformula Linking under Quantifiers'
<p>This is the artifact for the CPP '24 paper 'Unification for Subformula Linking under Quantifiers'. It contains formalizations of section 3.3 and section 4, as well as patches for Iris's improved version of iFrame.</p>
Data from: Cellects, a software to quantify cell expansion and motion
<p>Automated quantification offers unique opportunities to study biological phenomena, increasing reproducibility, replicability, accuracy, and throughput, while reducing observer biases. We present Cellects, a tool to quantify growth and motion in 2D. This software operates with image sequences containing specimens growing and moving on an immobile flat surface. Its user-friendly interface makes it easy to adjust the quantification parameters to cover a wide range of species and conditions, and includes tools to validate the results and correct mistakes if necessary. The software provides the region covered by the specimens at each point of time, as well as many geometrical descriptors that characterize it. We validated Cellects with <em>Physarum polycephalum</em>, which is particularly difficult to detect because of its complex shape and internal heterogeneity. This validation covered five different conditions with different background and lighting, and found Cellects to be highly accurate in all cases. Cellects' main strengths are its broad scope of action, automated computation of a variety of geometrical descriptors, easy installation and user-friendly interface.</p>
Quantifying the light-absorption properties and molecular composition of brown carbon aerosol from sub-Saharan African biomass combustion
<div> <p>Data presented in figures of the peer-reviewed journal article "Quantifying the light-absorption properties and molecular composition of brown carbon aerosol from sub-Saharan African biomass combustion" by Moschos et al.</p> <p>Disclaimer: Please contact the dataset creator prior to inclusion of data in any upcoming publication.</p> </div>
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.