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75
datasets available to search
ShareScore release 0.9.0
Dataset results
75 results for “spatiotemporal model”
A multi-scale model for hair follicle reveals heterogeneous skin domains drive rapid spatiotemporal hair growth patterning
GEO Series GSE85039. Mus musculus. 48 samples. Type: Expression profiling by high throughput sequencing.
Spatiotemporal Landscape in Kidney of A Mouse Model of Hyperuricemia at Single-Cell Level [single-cell sequencing]
GEO Series GSE256431. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Spatiotemporal Landscape in Kidney of A Mouse Model of Hyperuricemia at Single-Cell Level [spatial transcriptomics data]
GEO Series GSE258959. Mus musculus. 4 samples. Type: Other.
Modelled spatiotemporally explicit fish densities at different fisheries management scenarios
<ol> <li>Conflicts of interest between resource extraction and conservation are widespread, and negotiating such conflicts or trade-offs is a key issue for ecosystem managers. One such trade-off is resource competition between fisheries and marine top predators. Managing this trade-off has so far been difficult due to a lack of knowledge regarding the amount and distribution of prey required by top predators.</li> <li>Here, we develop a framework that can be used to address this gap: a bio-energetic model linking top predator breeding biology and foraging ecology with forage fish ecology and fisheries management.</li> <li>We apply the framework to a Baltic Sea colony of common guillemots <i>Uria aalge</i> and razorbills <i>Alca torda</i>, two seabird species sensitive to local prey depletion, and show that densities of forage fish (sprat <i>Sprattus sprattus</i> and herring <i>Clupea harengus</i>) corresponding to the current fisheries management target B<sub>MSY</sub> are sufficient for successful breeding. A previously proposed fisheries management target for conserving seabirds, 1/3 of historical maximum prey biomass (B<sub>1/3</sub>), was also sufficient.</li> <li>However, the results highlight the importance of maintaining sufficient prey densities in the vicinity of the colony, suggesting that fine-scale spatial fisheries management is necessary to maintain high seabird breeding success.</li> <li>Despite foraging on the same prey, razorbills could breed successfully at lower prey densities than guillemots but needed higher densities for self-maintenance, emphasizing the importance of considering species-specific traits when determining sustainable forage fish densities for top predators.</li> <li> <i>Synthesis and application.</i> Our bio-energetic modelling framework provides spatially explicit top predator conservation targets that can be readily integrated with current fisheries management. The framework can be combined with existing management approaches such as Dynamic Ocean Management, Marine Spatial Planning and Management Strategy Evaluation to inform ecosystem-based management of marine resources.</li> </ol>
Inverse estimation of spatiotemporal flux boundary conditions in unsaturated water flow modeling
<p>Data used in field case study in the paper titled "Inverse estimation of spatiotemporal flux boundary conditions in unsaturated water flow modeling".</p>
High Spatiotemporal Resolution Estimation of Global Surface CO Concentrations Using a Deep Learning Model
<p><span>A high-performance Convolutional Neural Network (CNN)-based Residual Network (ResNet) was developed for estimating daily worldwide CO concentrations at a high spatial resolution of 0.07</span><span>°</span><span> from June 2018 to May 2021, using the global TROPOMI Total Column of atmospheric CO (TCCO) product and reanalysis datasets. The proposed framework achieved a desirable estimation accuracy, with <em>R</em>-values (correlation coefficients) of 0.90 and 0.96 for daily and monthly predictions, respectively. The daily surface CO concentration dataset from our study is potentially useful for further relevant sustainable studies.</span></p>
Datasets and Model Predictions for "Scalable Spatiotemporal Prediction with Bayesian Neural Fields"
<p>This repository contains the evaluation datasets and model predictions that appear in the research article <em>Scalable Spatiotemporal Prediction with Bayesian Neural Fields</em> (Saad et al., 2024). Refer to the README files in each zip file for additional information.</p>
Modelling PM2.5 during severe atmospheric pollution episode in Lagos, Nigeria: Spatiotemporal variations, source apportionment, and meteorological influences
<p>Data</p>
Spatiotemporal Characteristics and Multi-body Dynamics Modeling Information After ACL Rupture and Reconstruction
ClinicalTrials.gov study NCT04462432. IPD Sharing: NO. Countries: 1. Publications: 0.
Spatiotemporal transcriptomic map of glial cell response in a mouse model of acute brain ischemia [snRNA-Seq]
GEO Series GSE233813. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Modelled spatiotemporally explicit fish densities at different fisheries management scenarios
Open the record for dataset details and reuse information.
Data from: Modeling spatiotemporal abundance of mobile wildlife in highly variable environments using boosted GAMLSS hurdle models
Open the record for dataset details and reuse information.
Spatiotemporal transcriptomic map of glial cell response in a mouse model of acute brain ischemia
GEO Series GSE233815. Mus musculus. 61 samples. Type: Expression profiling by high throughput sequencing; Other.
Spatiotemporally Controlled Restoration of GAS6 Signaling via mRNA Therapy Promotes Scarless Healing in Preclinical Models
GEO Series GSE309507. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Data and codes for Landslide hazard spatiotemporal modelling
<p>Data and codes for submissions</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.