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.
5,805
datasets available to search
ShareScore release 0.9.0
Dataset results
5,805 results for “Data model”
Data for the article: "Molecular Modelling Reveals Eight Novel Druggable Binding Sites in SARS-CoV-2's Spike Protein" by Ilke Ugur and Antoine Marion
<p>This upload contains data related to the article<br> published as a preprint on ChemRxiv with DOI<br> https://doi.org/10.26434/chemrxiv.13292768</p> <p>"Molecular Modelling Reveals Eight Novel Druggable Binding Sites in SARS-CoV-2's Spike Protein"<br> by Ilke Ugur and Antoine Marion (2020)<br> Department of Chemistry, Middle East Technical University, Ankara, Turkey.</p> <p>For further information, please contact:<br> ilkeugur@metu.edu.tr ; amarion@metu.edu.tr</p> <p>The manuscript is currently under peer-review.</p> <p>Content:</p> <p>Library of molecules derived from DrugBank v 5.1.5:<br> - DrugBank_2020_5.1.5/ # All necessary files for the docking and refinement of the library of molecules.<br> -- DB_5.1.5_pH7.4_pdbqt/ ## PDBQT readily usable for docking with AutoDock Vina.<br> -- DB_5.1.5_pH7.4_mol2amber/ ## mol2 files containing assigned GAFF atom types and Gasteiger atomic charges.<br> -- DB_5.1.5_pH7.4_frcmod/ ## frcmod files containing missing molecular mechanics parameters<br> -- dbID_name.dat ## DrugBank ID to generic name dictionary</p> <p>Note: The files were prepared automatically via a series of operations handling openbabel and antechamber.<br> The protonation state of ionizable groups as well as Gasteiger atomic charges were assigned by openbabel for a pH of 7.4<br> mol2 and frcmod files can be used readily via the tleap module of AmberTools to produce topology files.</p> <p><br> Receptor structures:<br> - receptors/ # PDB files for the four structures of the spike protein considered in this work<br> -- CS00ns.pdb ## Closed state after the remodelling of missing loops (PDB ID 6vxx)<br> -- OS00ns.pdb ## Open state after the remodelling of missing loops (PDB ID 6vyb)<br> -- CS25ns.pdb ## Closed state after 25 ns of molecular dynamics in explicit water<br> -- OS25ns.pdb ## Open state after 25 ns of molecular dynamics in explicit water</p> <p>Note: All structures are aligned to CS00ns.pdb and can be converted to pdbqt for docking with AutoDock Vina</p> <p><br> Docking grid centers:<br> - dockingCenters/ # XYZ files containing the coordinates of each docking grid center considered in this work</p> <p>Note: The coordinates are given in the same frame as that of the four structures of the receptor.</p> <p><br> Binding sites:<br> - bindingSites/ # XYZ files with the coordinates of the representative atomic centres<br> # of each binding site identified in this work (A-H).</p> <p>Note: These files can be used to get a clearer picture of the binding sites within the structures<br> of the spike protein shared in the receptors directory.</p> <p><br> Final modelling results:<br> - allData.txt # data for all molecules in the set (approved and investigational)<br> - appData.txt # data for approved molecules only<br> - data.xlsx # data for all molecules in the set (approved and investigational)<br> # as a formatted excel spreadsheet</p> <p>Note: The columns are delimited with semi-colons ";".<br> The files contain the results for the best pose of all approved molecules for which<br> molecular mechanics-based geometry optimization succeeded, regardless of their score.<br> For other molecules, the result of their best pose is reported only for those complexes<br> having MM interaction energy lower or equal to -22.00 kcal/mol.</p> <p><br> Visualization:<br> - bs.pse # pymol session representing the binding sites within the<br> # closed state structure of the spike protein (CS00ns)<br> - pt.pse # pymol session representing the docking grid centres within<br> # closed statestructure of the spike protein (CS00ns)</p> <p>Note: the PSE files should be compatible with version 7.0 of pymol and later</p>
Data, Sensitivity of 21st-century projected ocean new production changes to idealized biogeochemical model structure
<p>Data for reproducing figures in journal article submitted to Biogeosciences in December 2020.</p> <p>Data generated from global 1-degree simulations of the CESM in an ocean-ice configuration.</p> <p>NP model by Brett. See 10.5281/zenodo.4361705 for code for NP model and to use this dataset to recreate paper figures.</p>
Measurement and model data comparisons for the HALO-FAAM formation flight during EMeRGe on 17 July 2017
<p>Within the project “Effect of Megacities on the transport and transformation of pollutants on the Regional and Global scales” (EMeRGe), the measurement flight of 13 July 2017 was performed for comparison of the instrumentation onboard of the research aircraft HALO and FAAM. The aircraft flew for 1.6 h in close formation along a racetrack pattern at three flight levels in Southern Germany. The flight started in a rather dry and clean troposphere and ended in a more polluted convective boundary layer. 28 measurement pairs sampled on both aircraft were found suitable for comparison. 17 further pairs of data are available from sampling on either HALO or FAAM. In addition, observations obtained at the DWD Hohenpeissenberg and results from 6 models are included in the comparisons. Overall, about 30% of the measured data pairs show deviations within the combined error estimates. Some measurements deviate considerably from model results.</p> <p>This dataset contains a pdf of the report and a zip file of the comparison data as described in that report.</p>
Smart Building Model (SBuM) Data
<p>This dataset is to be used in conjonction with the SBuM model available online at:</p> <p>https://github.com/jeanlouisnico/SBuM</p> <p>Download add the file into the path of your MatLab environment to allow MatLab to locate the files.</p> <p>v1.1: added the zip file that it is easier to download all the files at once.</p>
Data for: Geometrical parameters for musculoskeletal modeling of hand
<p>Dataset to be linked with not yet published manuscript "Geometrical parameters for<br> musculoskeletal modeling of hand"</p> <p>In musculoskeletal modelling, parameters identification, such as the exact position and trajectories of muscle attachments, is a crucial issue. The main goal of this study was to calculate the position, attachment dimensions and cross section areas of twenty-five extrinsic and intrinsic hand muscle complexes. We integrated measurements taken from cadaveric preparations, magnetic resonance imaging and mathematical theory. Sixteen cadaveric preparations were dissected to draw up the anatomical maps including the position of muscle attachments, dimensions, shapes, cross section areas and variations. The magnetic resonance imaging of cadaveric upper extremity was performed to reconstruct the geometry of all bones and hand muscles. Using these outcomes, the muscle attachments and cross section areas were extracted and verified using the obtained morphological and morphometric analysis. The exact trajectories of muscle lines of action were computed using the modified weighted k-means method and Hungary algorithm. This work introduces a new approach to acquiring musculoskeletal modelling data in general and contributes extensive dataset to the hand musculature modelling in particular.</p> <p><strong>Acknowledgments</strong></p> <p>This work was supported by the project n. 182 “Obstetrics 2.0 - Virtual models for the prevention of injuries during childbirth” realised within the frame of the Program INTERREG V-A: Cross- border cooperation between the Czech Republic and the Federal State of Germany Bavaria, Aim European Cross-border cooperation 2014-2020. The realisation is supported by financial means of the European Regional Development Fund (85 % of the costs) and the state budget of the Czech Republic (5 %). KI is part-funded by project No. CZ.02.1.01/0.0/0.0/16_019/0000787 “Fighting INfectious Diseases“, awarded by the Ministry of Education, Youth and Sports of the Czech Republic, financed from The European Regional Development Fund.</p>
Ultrasonic guided-wave experiment data for manuscript entitled 'A homogenisation scheme for Lamb ultrasound wave dispersion in textilecomposites through multiscale wave and finite element modelling'
<p>This data set contains the ultrasonic guided wave signals (signal amplitudes as a function of time for different sensors) that were generated and recorded using the transducers and controlling instrument in support of the manuscript entitled 'A homogenisation scheme for Lamb ultrasound wave dispersion in textile composites through multiscale wave and finite element modelling'. The controlling software was programmed in MATLAB and that the attached files are in accordance to the .mat file format.</p> <p>The file names follow the notation described below with an example:</p> <p>S1_10kHz_2cyc (illustrated with an example): S1 represents the number of sensors; 10kHz represents the exciting frequency; 2cyc represents the cycle number of input waveform.</p> <p>Details on the experiment setup are provided within an extra file ('Readme' file).</p>
Experimental data in support of manuscript entitled 'A homogenisation scheme for Lamb ultrasound wave dispersion in textile composites through multiscale wave and finite element modelling'
<p>This data set contains the ultrasonic guided wave signals (signal amplitudes as a function of time for different sensors) that were generated and recorded using the transducers and controlling instrument in support of the manuscript entitled 'A homogenisation scheme for Lamb ultrasound wave dispersion in textile composites through multiscale wave and finite element modelling'. The controlling software was programmed in MATLAB and that the attached files are in accordance to the .mat file format.</p> <p>The file names follow the notation described below with an example:</p> <p>S1_10kHz_2cyc (illustrated with an example): S1 represents the number of sensors; 10kHz represents the exciting frequency; 2cyc represents the cycle number of input waveform.</p> <p>Details on the experiment setup are provided within an extra file ('Readme' file).</p>
Data from: Temperature drives Zika virus transmission: evidence from empirical and mathematical models
<p>Temperature is a strong driver of vector-borne disease transmission. Yet, for emerging arboviruses we lack fundamental knowledge on the relationship between transmission and temperature. Current models rely on the untested assumption that Zika virus responds similarly to dengue virus, potentially limiting our ability to accurately predict the spread of Zika. We conducted experiments to estimate the thermal performance of Zika virus (ZIKV) in field-derived Aedes aegypti across eight constant temperatures. We observed strong, unimodal effects of temperature on vector competence, extrinsic incubation period, and mosquito survival. We used thermal responses of these traits to update an existing temperature-dependent model to infer temperature effects on ZIKV transmission. ZIKV transmission was optimized at 29oC, and had a thermal range of 22.7oC - 34.7oC. Thus, as temperatures move toward the predicted thermal optimum (29oC) due to climate change, urbanization, or seasonally, Zika could expand north and into longer seasons. In contrast, areas that are near the thermal optimum were predicted to experience a decrease in overall environmental suitability. We also demonstrate that the predicted thermal minimum for Zika transmission is 5oC warmer than that of dengue, and current global estimates on the environmental suitability for Zika are greatly over-predicting its possible range.</p>
Data from: Continuous-time spatially explicit capture-recapture models, with an application to a jaguar camera-trap survey
<ol> <li>Many capture-recapture surveys of wildlife populations operate in continuous time but detections are typically aggregated into occasions for analysis, even when exact detection times are available. This discards information and introduces subjectivity, in the form of decisions about occasion definition.</li> <li>We develop a spatio-temporal Poisson process model for spatially explicit capture-recapture (SECR) surveys that operate continuously and record exact detection times. We show that, except in some special cases (including the case in which detection probability does not change within occasion), temporally aggregated data do not provide sufficient statistics for density and related parameters, and that when detection probability is constant over time our continuous-time (CT) model is equivalent to an existing model based on detection frequencies. We use the model to estimate jaguar density from a camera-trap survey and conduct a simulation study to investigate the properties of a CT estimator and discrete-occasion estimators with various levels of temporal aggregation. This includes investigation of the effect on the estimators of spatio-temporal correlation induced by animal movement.</li> <li>The CT estimator is found to be unbiased and more precise than discrete-occasion estimators based on binary capture data (rather than detection frequencies) when there is no spatio-temporal correlation. It is also found to be only slightly biased when there is correlation induced by animal movement, and to be more robust to inadequate detector spacing, while discrete-occasion estimators with binary data can be sensitive to occasion length, particularly in the presence of inadequate detector spacing.</li> <li>Our model includes as a special case a discrete-occasion estimator based on detection frequencies, and at the same time lays a foundation for the development of more sophisticated CT models and estimators. It allows modelling within-occasion changes in detectability, readily accommodates variation in detector effort, removes subjectivity associated with user-defined occasions, and fully utilises CT data. We identify a need for developing CT methods that incorporate spatio-temporal dependence in detections and see potential for CT models being combined with telemetry-based animal movement models to provide a richer inference framework.</li> </ol>
Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift
<p>The Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>) is native to Southeast Asia. Since its first detection in 2008 in Europe and North America, it has been a pest to the fruit production industry as it feeds and oviposits on ripening fruit. Here we aim to model the potential geographical distribution of <em>D. suzukii</em>. We performed an extensive literature review to map the current records. In total, 517 documented occurrences (96 native and 421 invasive) were identified spanning 52 countries. Next, we constructed three species distribution models (SDMs) based on occurrence records in: 1) the native range (SDMnative), 2) the invasive range in Europe (SDMEurope) and 3) a global model of all records (SDMglobal). The models aimed to investigate, whether this species will be able to occupy additional ecological niches beyond its native range and expand its current geographic distribution both globally and in Europe. The SDMs were generated using Maximum Entropy algorithms (Maxent) based on present occurrence records and bioclimatic variables (WorldClim). Predictions of habitat suitability vary greatly depending on the origins of occurrence records. According to all models, precipitation and low temperatures were key limiting factors for the distribution of <em>D. suzukii</em>, which suggests that this species requires a humid environment with mild winters in order to establish a permanent population in its invasive range. Several regions in the invasive range, not presently occupied by this species, were predicted highly suitable, especially in northern Europe, suggesting that <em>D. suzukii</em> is not occupying its full fundamental niche yet. Synthesis and applications. Based on these models of potential geographic distribution of the Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>), we show a shift in the ecological niche in <em>D. suzukii</em> populations, emphasizing the importance of using presence and local environmental data. Further investigation regarding new occurrences is recommended to secure optimal pest management. Despite a continuing expansion, many countries still lack proper surveillance schemes, and we urge policymakers to initiate appropriate management programs.</p>
Data from: Neural representation of bat predation risk and evasive flight in moths: a modelling approach
<p>Most animals are at risk from multiple predators and can vary anti-predator behaviour based on the level of threat posed by each predator. Animals use sensory systems to detect predator cues, but the relationship between the tuning of sensory systems and the sensory cues related to predator threat are not well-studied at the community level. Noctuid moths have ultrasound-sensitive ears to detect the echolocation calls of predatory bats. Here, combining empirical data and mathematical modelling, we show that moth hearing is adapted to provide information about the threat posed by different sympatric bat species. First, we found that multiple characteristics related to the threat posed by bats to moths correlate with bat echolocation call frequency. Second, the frequency tuning of the most sensitive auditory receptor in noctuid moth ears provides information allowing moths to escape detection by all sympatric bats with similar safety margin distances. Third, the least sensitive auditory receptor usually responds to bat echolocation calls at a similar distance across all moth species for a given bat species. If this neuron triggers last-ditch evasive flight, it suggests that there is an ideal reaction distance for each bat species, regardless of moth size. This study shows that even a very simple sensory system can adapt to deliver information suitable for triggering appropriate defensive reactions to each predator in a multiple predator community.</p>
Data from: Complementary strengths of spatially-explicit and multi-species distribution models
<p><span><span><span><span><span><span><span><span><span><span><span> Species distribution models (SDMs) project the outcome of community assembly processes - dispersal, the abiotic environment, and biotic interactions - onto geographic space. Recent advances in SDMs account for these processes by simultaneously modeling the species that comprise a community in a multivariate statistical framework or by incorporating residual spatial autocorrelation in SDMs. However, the effects of combining both multivariate and spatially-explicit model structures on the ecological inferences and the predictive abilities of a model are largely unknown. We used data on eastern hemlock (<i>Tsuga canadensis</i>L.) and five additional co-occurring overstory tree species in 35,569 forest stands across Michigan, USA to evaluate how the choice of model structure, including spatial and non-spatial forms of univariate and multivariate models, affects ecological inference about the processes that shape community composition as well as model predictive ability.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span> Incorporating residual spatial autocorrelation via spatial random effects did not improve out-of-sample prediction for the six tree species, although in-sample model fit was higher in the spatial models. Spatial models attributed less variation in occurrence probability to environmental covariates than the non-spatial models for all six tree species, and estimated higher (more positive) residual co-occurrence values for most species pairs. The non-spatial multivariate model was better suited for evaluating habitat suitability and hypotheses about the processes that shape community composition. Environmental correlations and residual correlations among species pairs were positively related, perhaps indicating that residual correlations were due to shared responses to unmeasured environmental covariates. This work highlights the importance of choosing a non-spatial model formulation to address research questions about the species-environment relationship or residual co-occurrence patterns, and a spatial model formulation when within-sample prediction accuracy is the main goal.</span></span></span></span></span></span></span></span></span></span></p>
Data for Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications
<p>These data were generated for the Open-Acces Article :</p> <p>Kamerling, S.; Vuillerme, V.; Rodat, S. Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications. <em>Energies</em> <strong>2021</strong>, <em>14</em>, 3731. https://doi.org/10.3390/en14133731</p> <p>In these dataset, the data for the Case Study and the Sensitivity Analysis are available. Jupyter Notebooks for further process of these data are also available. The NoteBooks AnalyseHourlyValues, AnalyseDailyValues and AnalyseMonthlyValues allow for easy change of variable, whereas CaseStudyAnalysis is for one specific set of data. The AnalyseSets were created in order to analyse the influence of the optimization on the solar fraction of the different datasets.</p>
Data from: Spatial processes and evolutionary models: a critical review
Evolution is a fundamentally population level process in which variation, drift, and selection produce both temporal and spatial patterns of change. Statistical model fitting is now commonly used to estimate which kind of evolutionary process best explains patterns of change through time, using models like Brownian motion, stabilizing selection (Ornstein-Uhlenbeck), and directional selection on traits measured from stratigraphic sequences or on phylogenetic trees. But these models assume that the traits possessed by a species are homogeneous. Spatial processes such as dispersal, gene flow, and geographic range changes can produce patterns of trait evolution that do not fit the expectations of standard models, even when evolution at the local-population level is governed by drift or a typical OU model of selection. The basic properties of population level processes (variation, drift, selection, and population size) are reviewed and the relationship between their spatial and temporal dynamics is discussed. Typical evolutionary models used in palaeontology incorporate the temporal component of these dynamics, but not the spatial. Range expansions and contractions introduce rate variability into drift processes, range expansion under a drift model can drive directional change in trait evolution, and spatial selection gradients can create spatial variation in traits that can produce long-term directional trends and punctuation events depending on the balance between selection strength, gene flow, extirpation probability, and model of speciation. Using computational modelling that spatial processes can create evolutionary outcomes that depart from basic population-level notions from these standard macroevolutionary models.
BrainSignals Revisited - Models & Data
<p>Model definitions, input files and data used for the model simplifications described in the paper <em>BrainSignals Revisited.</em></p>
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>
Supporting data: Reporting phenotypes in model organisms when considering body size as a potential confounder.
<p>This directory contains the data and associated scripts used to generate the figures in the manuscript "Reporting phenotypes in model organisms when considering body size as a potential confounder." submitted to the Journal of Biomedical Semantics</p>
Modeling sympathetic cooling of molecules by ultracold atoms: supporting data
<p>Data used in preparation of the paper "Modeling sympathetic cooling of molecules by ultracold atoms", authored by Jongseok Lim, Matthew D. Frye, Jeremy M. Hutson and M. R. Tarbutt.</p> <p>There are four different types of data:</p> <p>(1) Tables of total cross sections versus collision energy for collisions of CaF with Li and Rb for various values of s-wave scattering length (see figure 1)</p> <p>(2) Tables of differential cross sections versus energy for collisions of CaF with Li and Rb for various values of s-wave scattering length. The differential cross sections are given as cumulative distribution functions.</p> <p>(3) Simulated kinetic energy distributions at 1s intervals for sympathetic cooling of CaF with Li and Rb for various values of s-wave scattering length (see figures 5 and 6).</p> <p>(4) Simulated kinetic energy distributions at 1s intervals for sympathetic cooling of CaF with Rb with various evaporative cooling ramps applied to the Rb (see figure 13).</p>
Data and code for "A Signal-Detection Approach to Modeling Forgiveness Decisions"
<p>Contains the data and code that supplements the journal article, "A Signal-Detection Approach to Modeling Forgiveness Decisions".</p> <p>Article doi: 10.1016/j.evolhumbehav.2016.06.004</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.