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567
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ShareScore release 0.9.0
Dataset results
567 results for “Simulated datasets”
Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning: W+jet training/test dataset
<p>W+jet events at generator and reconstruction level, used to train analysis-specific generative models.</p> <p>Events are represented as an array of relevant high-level features. Reco objects are matched to Gen objects and a minimal selection is applied to define the generator support in the N-dim space identified by the input features.</p> <p>About 2M events, used for training/validation/testing</p> <p>Details in https://arxiv.org/abs/2010.01835</p>
Hierarchical Inference With Bayesian Neural Networks: An Application to Strong Gravitational Lensing - Model Weights, Chains, BNN Samples, and Simulated Datasets
<p>The model weights, chains, simulated datasets, and BNN samples used to produce the results shown in LSST DESC Collaboration paper "Hierarchical Inference With Bayesian Neural Networks: An Application to Strong Gravitational Lensing." All files presented here are meant for use in tandem with the python package "ovejero" (<a href="https://github.com/swagnercarena/ovejero">https://github.com/swagnercarena/ovejero</a>).</p>
Mating under climate change: impact of simulated heatwaves on the reproduction of model pollinators (Dataset)
<ol> <li>Climate change is related to an increase in frequency and intensity of extreme events such as heatwaves. It is well established that such events may worsen the current worldwide biodiversity decline. In many organisms, heat stress is associated with direct physiological perturbations and could lead to a decrease of fitness. In contrast to endotherms, heat stress resistance has been poorly investigated in heterotherms; especially in insects, in which the internal physiological mechanisms available to regulate body temperature are almost negligible making them sensitive to extreme temperature variations.</li> <li>Wild bees are crucial pollinators for wild plants and crops. Among them, bumblebees are experiencing a strong decline across the world. Therefore, the ongoing global decline of these insect pollinators partly due to climate change could cause major economic issues.</li> <li>Here, we assess how simulated heatwaves impact fertility and attractiveness (key parameters of sustainability) of bumblebee males. We used three model species: <i>Bombus terrestris</i>, a widespread and warm-adapted species, <i>B. magnus</i> and <i>B. jonellus</i>, two declining and cold-adapted species.</li> <li>We highlight that heat shock (40°C) negatively affects sperm viability and sperm DNA integrity only in the two cold-adapted species. Heat shock can also impact the structure of cephalic labial glands and the production of pheromones only in the declining species.</li> <li>The specific disruption in key reproductive traits we identify following simulated heatwave conditions could provide one important mechanistic explanation for why some pollinators are in decline through climate change.</li> </ol>
Datasets used in "Large Eddy Simulation for Investigating Coupled Forest Canopy and Turbulence Influences on Atmospheric Chemistry"
<p>Model archived fields used in the generation of the figures in: Clifton, O. E., E. G. Patton, S. Wang, M. Barth, J. Orlando, R. H. Schwantes (2022), Large Eddy Simulation for Investigating Coupled Forest Canopy and Turbulence Influences on Atmospheric Chemistry, Journal of Advances in Modeling Earth Systems.</p>
Datasets associated with the manuscript "Discovering SARS-CoV-2 neoepitopes and the associated TCR-pMHC recognition mechanisms by combining single-cell sequencing, deep learning, and molecular dynamics simulation techniques"
<p>meta_data_TCR-pMHC_from_STCRDab.tsv, TCR-pMHC structures used for contacts analysis.</p><p>tcr_gliph_input_sars2.tsv, input files (TCR sequences and related information) used for clustering TCRs targeting SARS-CoV-2 epitopes and epitope-unknown TCRs.</p><p>tcr_gliph_input_non-sars2.tsv, input files used for clustering TCRs targeting non-SARS-CoV-2 epitopes and epitope-unknown TCRs.</p><p>tcr_gliph_output*, output files from the GLIPH software, including the recognized TCR clusters by GLIPH (convergence-group.txt), the linkage information of TCR clusters (clone-network.txt), and the recognized motif in TCR clusters (kmer.txt).</p><p>md_trajs.tar, structures and MD simulation trajectories of TCR-614-pMHC and TCR-204-pMHC complexes.</p>
Dataset for manuscript: Boosting ensemble refinement with transferable force field corrections: synergistic optimization for molecular simulations
<p>See https://github.com/bussilab/force-field-ensemble-refinement for analysis scripts</p>
Dataset for "Linear theory analysis and one-dimensional hybrid simulations of high-frequency EMIC waves in a dipole magnetic field"
<p>Processed dataset to produce the figures in the manuscript</p>
Dataset for "Application of Digital Twins for Simulation Based Tailoring of Laser Induced Graphene"
Open the record for dataset details and reuse information.
Three datasets containting the solutions of FEA simulations for a 2D Linear Elastic Model, a 2D Hyperelastic Model and a 3D Linear Elastic Model
Open the record for dataset details and reuse information.
FETCH4 Simulation Datasets
Open the record for dataset details and reuse information.
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in future climate (2069-2098, RCP 8.5), Kortrijk Kennedy Park, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Kortrijk Kenny Park (50° 48' 2"N 3°16'13" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098, RCP 8.5 climate change scenario) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the future period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Sint-Katelijne-Waver, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Sint-Katelijne-Waver (51°3'25"N 4°11'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
The simulation datasets
<p>The transcriptome simulation datasets</p>
Pathways, form drag, and turbulence in a simulated ocean flowing through through an ice melange: datasets
<p>Data associated with Hughes (2022). <em>J. Geophys. Res. </em><a href="https://doi.org/10.1029/2021JC018228">doi:10.1029/2021JC018228</a></p> <p>This archive contains</p> <ol> <li>Output from all model simulations together with a summary csv file. Full details in <strong>melange_flow_simulations_readme.pdf</strong></li> <li>A directory (<strong>icebergs.zip</strong>) containing the scripts necessary to reproduce model outputs described in the paper.</li> </ol> <p> </p>
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.5% spike-in contaminant sequences
<p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p> <p> </p> <p>Simulation Dataset 0.5% contaminant spike-in. </p>
Datasets of GRMHD Simulations of Accreting Neutron Stars with Non-Dipole Fields
<p>Datasets for GRMHD Simulations of Accreting Neutron Stars with Non-Dipole Fields</p>
Five-Spin Supramolecule for Simulating Quantum Decoherence of Bell States. Open dataset
<p>Data supporting the original figures 2, 3, 4 of the related publication.</p>
Li Simulation Dataset
<p>I have uploaded three dataset files.</p>
Dataset and simulation file associated with the paper "International climate finance and emission reductions: What do the last twenty years tell us?", by C. Gavard and N. Schoch
<p>Dataset and simulation file associated with the paper "International climate finance and emission reductions: What do the last twenty years tell us?", by C. Gavard and N. Schoch</p> <p>For details, see readme file</p>
Dataset for: Numerical simulations of sheared granular materials by 3D DEM for analyzing formation of internal structures and relationship between it and frictional behavior
<p>We conducted numerical simulations of sheared granular materials under normal stress by using 3D DEM method in order to analyze internal structures and relationship between their formation and frictional behavior. This dataset includes raw data for plotting figures in our article and run scripts and CAD files for simulations.</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.