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60 results for “multiscale modeling”
Data set associated with the paper "Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere for Use in the Quasi-3-D Multiscale Modeling Framework"
<p>New data set associated with the revision of the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework: <br> I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"</p> <p>The title of the paper has been changed to "Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere for Use in the Quasi-3-D Multiscale Modeling Framework"</p> <p>New simulated data set of the advection test is in the folder ADVEC_NEW; New simulated data set of the barotropic instability test is in the folder BARO_NEW; New simulated data set of the baroclinic instability test is in the folder BCL_NEW</p>
Dataset for the article "MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry"
<p>This dataset contains additional material related to the article: "MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry". The preprint is available at <a href="https://doi.org/10.26434/chemrxiv.7635986">https://doi.org/10.26434/chemrxiv.7635986</a>. Final article is available at <a href="https://doi.org/10.1021/acs.jctc.9b00093">https://doi.org/10.1021/acs.jctc.9b00093</a>.</p>
Data from: A multiscale biophysical model for the recruitment of actin nucleating proteins at the membrane interface
Open the record for dataset details and reuse information.
Derived variables and coordinates to assess the ecological relevance of multiscale bathymetry for coral species distribution modelling across the Great Barrier Reef
Open the record for dataset details and reuse information.
Elevation Models for Reproducible Evaluation of Terrain Representation – Multiscale Models – Valdez ASCII
<p>Multiscale elevation models centered on Valdez, Alaska, USA</p> <p>Resolutions: 3.3, 7.5, 15, 30, 90, 250, 500, 1,000, and 2,000 meters, 1500 x 1,500 height samples each</p> <p>File format: Esri ASCII grid</p> <p>When using these elevation models in an academic publication, please cite the following article, which describes the process and rationale for compiling these models:</p> <p><em>Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a></em></p>
Elevation Models for Reproducible Evaluation of Terrain Representation – Multiscale Models – Gore Range GeoTIFF
<p>Multiscale elevation models centered on Gore Range, Colorado, USA</p> <p>Resolutions: 1, 5, 15, 30, 90, 250, 500, 1,000, 2,000, 2,500, and 5,000 meters, 1500 x 1,500 height samples each</p> <p>File format: GeoTIFF</p> <p>When using these elevation models in an academic publication, please cite the following article, which describes the process and rationale for compiling these models:</p> <p><em>Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a></em></p>
Elevation Models for Reproducible Evaluation of Terrain Representation – Multiscale Models – Gore Range ASCII
<p>Multiscale elevation models centered on Gore Range, Colorado, USA</p> <p>Resolutions: 1, 5, 15, 30, 90, 250, 500, 1,000, 2,000, 2,500, and 5,000 meters, 1500 x 1,500 height samples each</p> <p>File format: Esri ASCII grid</p> <p>Version 1.1.0 does not contain GeoTIFF files that were included by mistake in version 1.0.0.</p> <p>When using these elevation models in an academic publication, please cite the following article, which describes the process and rationale for compiling these models:</p> <p><em>Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a></em></p>
Multiscale heart image data for: Multiscale cardiac imaging spanning the whole heart and its internal cellular architecture in a small animal model
<p>Cardiac pumping depends on the morphological structure of the heart, but also on its sub-cellular (ultrastructural) architecture, which enables cardiac contraction. In cases of congenital heart defects, localized ultrastructural disruptions that increase the risk of heart failure are only starting to be discovered. This is in part due to a lack of technologies that can image the three dimensional (3D) heart structure, assessing malformations; and its ultrastructure, assessing disruptions. We present here a multiscale, correlative imaging procedure that achieves high-resolution images of the whole heart, using 3D micro-computed tomography (micro-CT); and its ultrastructure, using 3D scanning electron microscopy (SEM). We achieved uniform fixation and staining of the whole heart, without losing ultrastructural preservation on the same sample, enabling correlative multiscale imaging. Our approach enables multiscale studies in models of congenital heart disease and beyond.</p>
Data associated with Cell Reports publication: Dura-Bernal, Griffith, et al. 2023, "Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics" (2/4)
<p>This dataset includes experimental data used to constrain and validate the model, and model simulation output data for the following Cell Reports publication: <a href="https://www.cell.com/cell-reports/fulltext/S2211-1247(23)01390-6">https://www.cell.com/cell-reports/fulltext/S2211-1247(23)01390-6</a></p><p>The source code for the associated A1 model and data analysis can be found here: <a href="https://github.com/NathanKlineInstitute/Macaque_auditory_thalamocortical_model_data">https://github.com/NathanKlineInstitute/Macaque_auditory_thalamocortical_model_data</a>.</p><p>All zip files should unzipped into a parent folder called /data inside the Github repository above.</p><p><strong>Important:</strong> Due to the Zenodo size limit, this dataset is split among 4 Zenodo uploads. This is upload <strong>2 out of 4</strong>. The other 3 uploads can be found at: </p><p>Upload 1/4: <a href="http://doi.org/10.5281/zenodo.10066993">http://doi.org/10.5281/zenodo.10066993</a> (https://zenodo.org/uploads/10066993)</p><p>Upload 3/4: <a href="http://doi.org/10.5281/zenodo.10071726">http://doi.org/10.5281/zenodo.10071726</a> (https://zenodo.org/uploads/10071726)</p><p>Upload 4/4: <a href="http://doi.org/10.5281/zenodo.10072277">http://doi.org/10.5281/zenodo.10072277</a> (https://zenodo.org/uploads/10072277)</p><p>For more information please contact: salvador.dura-bernal@downstate.edu </p>
Data associated with Cell Reports publication: Dura-Bernal, Griffith, et al. 2023, "Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics" (3/4)
<p>This dataset includes experimental data used to constrain and validate the model, and model simulation output data for the following Cell Reports publication: <a href="https://www.cell.com/cell-reports/fulltext/S2211-1247(23)01390-6">https://www.cell.com/cell-reports/fulltext/S2211-1247(23)01390-6</a></p><p>The source code for the associated A1 model and data analysis can be found here: <a href="https://github.com/NathanKlineInstitute/Macaque_auditory_thalamocortical_model_data">https://github.com/NathanKlineInstitute/Macaque_auditory_thalamocortical_model_data</a>.</p><p>All zip files should unzipped into a parent folder called /data inside the Github repository above.</p><p><strong>Important:</strong> Due to the Zenodo size limit, this dataset is split among 4 Zenodo uploads. This is upload <strong>3 out of 4</strong>. The other 3 uploads can be found at: </p><p>Upload 1/4: <a href="http://doi.org/10.5281/zenodo.10066993">http://doi.org/10.5281/zenodo.10066993</a> (https://zenodo.org/uploads/10066993)</p><p>Upload 2/4: <a href="http://doi.org/10.5281/zenodo.10069553">http://doi.org/10.5281/zenodo.10069553</a> (https://zenodo.org/uploads/10069553)</p><p>Upload 4/4: <a href="http://doi.org/10.5281/zenodo.10072277">http://doi.org/10.5281/zenodo.10072277</a> (https://zenodo.org/uploads/10072277)</p><p>For more information please contact: salvador.dura-bernal@downstate.edu </p>
Data associated with Cell Reports publication: Dura-Bernal, Griffith, et al. 2023, "Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics" (1/4)
<p>This dataset includes experimental data used to constrain and validate the model, and model simulation output data for the following Cell Reports publication: <a href="https://www.cell.com/cell-reports/fulltext/S2211-1247(23)01390-6">https://www.cell.com/cell-reports/fulltext/S2211-1247(23)01390-6</a></p><p>The source code for the associated A1 model and data analysis can be found here: <a href="https://github.com/NathanKlineInstitute/Macaque_auditory_thalamocortical_model_data">https://github.com/NathanKlineInstitute/Macaque_auditory_thalamocortical_model_data</a>.</p><p>All zip files should unzipped into a parent folder called /data inside the Github repository above.</p><p><strong>Important:</strong> Due to the Zenodo size limit, this dataset is split among 4 Zenodo uploads. This is upload <strong>1 out of 4</strong>. The other 3 uploads can be found at: </p><p>Upload 2/4: <a href="http://doi.org/10.5281/zenodo.10069553">http://doi.org/10.5281/zenodo.10069553</a> (https://zenodo.org/uploads/10069553)</p><p>Upload 3/4: <a href="http://doi.org/10.5281/zenodo.10071726">http://doi.org/10.5281/zenodo.10071726</a> (https://zenodo.org/uploads/10071726)</p><p>Upload 4/4: <a href="http://doi.org/10.5281/zenodo.10072277">http://doi.org/10.5281/zenodo.10072277</a> (https://zenodo.org/uploads/10072277)</p><p>For more information please contact: salvador.dura-bernal@downstate.edu </p>
United Atom Parameters for United Atom Multiscale Modelling Of Bio-Nano Interactions Of PEG Coated Nanoparticles
<p>Short-range surface adsorption potentials of carbohydrates, lipid fragments, and amino acid side chains in tabulated form.</p><p>Recovered from radial distribution functions</p><p>Force Fields: adapted CHARMM36.</p><p>Material: PEG</p><p>Status: updated on November 6, 2023</p>
Characterizing the complexity of subduction zone flow with an ensemble of multiscale global convection models
<p>Parameter files and model input .txt files for ASPECT mantle convection simulations.</p>
United Atom Parameters for United Atom Multiscale Modelling Of Bio-Nano Interactions Of Zero-Valent Silver Nanoparticles
<p>Short-range surface adsorption potentials of carbohydrates, lipid fragments, and amino acid side chains in tabulated form.</p> <p>Calculated via AWT-MetaD (Gromacs/Plumed).</p> <p>Force Fields: INTERFACE/CHARMM36.</p> <p>Material: zero-valent silver</p>
i-Tasser 3D Strucutres of Blood Plasma Proteins for United Atom Multiscale Modelling Of Bio-Nano Interactions
<p>3D Structures of blood plasma proteins as per proteomic data on protein corona for AgNPs presented in this publication:</p> <blockquote> <p>Gorshkov V, Bubis JA, Solovyeva EM, Gorshkov M, KjeldsenF. Protein corona formed on silver nanoparticles in blood plasma is highly selective and resistant to physicochemical changes of the solution. Environ. Sci.: Nano, 2019,6, 1089-1098. doi: 10.1039/C8EN01054D</p> </blockquote> <p>Note, that the dataset is different from the one used in this publication:</p> <blockquote> <p>Alsharif SA, Power D, Rouse I, Lobaskin V. In Silico Prediction of Protein Adsorption Energy on Titanium Dioxide and Gold Nanoparticles. Nanomaterials (Basel). 2020 Oct 4;10(10):1967. doi: 10.3390/nano10101967.</p> </blockquote> <p>Files were prepared with I-TASSER utility:</p> <blockquote> <p>J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure and function prediction. Nature Methods, 12: 7-8 (2015).</p> </blockquote> <p> </p>
United Atom Parameters for United Atom Multiscale Modelling Of Bio-Nano Interactions Of Zero-Valent Copper Nanoparticles
<p>Short-range surface adsorption potentials of carbohydrates, lipid fragments, and amino acid side chains in tabulated form.</p> <p>Calculated via AWT-MetaD (Gromacs/Plumed).</p> <p>Force Fields: INTERFACE/CHARMM36.</p> <p>Material: zero-valent copper</p>
i-Tasser 3D Strucutres of Milk Proteins for United Atom Multiscale Modelling Of Bio-Nano Interactions
<p>The list of milk proteins was obtained from this work:</p> <blockquote> <p>Tacoma R, Fields J, Ebenstein DB, Lam YW, Greenwood SL. Characterization of the bovine milk proteome in early-lactation Holstein and Jersey breeds of dairy cows. Journal of Proteomics, 2016 (130), 200-210.</p> </blockquote> <p>Files were prepared with I-TASSER utility:</p> <blockquote> <p>J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure and function prediction. Nature Methods, 12: 7-8 (2015).</p> </blockquote>
United Atom Parameters for United Atom Multiscale Modelling Of Bio-Nano Interactions Of Citrate Trianion Stabilized Nanoparticles
<p>Short-range surface adsorption potentials of carbohydrates, lipid fragments, and amino acid side chains onto Cit(3-) stabilized surfaces (in tabulated form).</p> <p>Recovered from radial distribution functions</p> <p>Force Fields: adapted CHARMM36.</p> <p>Material: CIT(3-)</p>
United Atom Parameters for United Atom Multiscale Modelling Of Bio-Nano Interactions Of Zero-Valent Gold Nanoparticles
<p>Short-range surface adsorption potentials of carbohydrates, lipid fragments, and amino acid side chains in tabulated form.</p> <p>Calculated via AWT-MetaD (Gromacs/Plumed).</p> <p>Force Fields: INTERFACE/CHARMM36.</p> <p>Material: zero-valent gold</p>
Tool and python programs for the paper "The Impact of Altering Emission Data Precision on Compression Efficiency and Accuracy of Simulations of the Community Multiscale Air Quality Model"
<p>Here is the content:</p> <p> * file dir_list which contains information about each file's content</p> <p> * the tool is used to alter a data file by keeping a specific number of significant digits for the paper "The Impact of Altering Emission Data Precision on Compression Efficiency and Accuracy of Simulations of the Community Multiscale Air Quality Model'</p> <p> * pythons program and its associated data to create each figure and table in the paper (data for Table 07 is not included due to size is larger than 50GB)</p>
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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.