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392
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ShareScore release 0.7.1
Dataset results
392 results for “tutorial”
Supplementary information for the manuscript 'GFViz: A tutorial on creating interactive visualization of genomic features using R Tidyverse and plotly'
<p>This is the supplementary information of the manuscript 'GFViz: A tutorial on creating interactive visualization of genomic features using R Tidyverse and plotly' published as a part of the thesis 'Annotating and making use of the <em>Avena sativa</em> cv. Sang reference genome' by Nikos Tsardakas Renhuldt.</p>
PyThia Scatterometry Tutorial Data
<p>Data set for PyThia scatterometry tutorial.</p>
MIntO - Tutorial Dataset
<p>Dataset for MIntO tutorial</p>
Cloud Factory - Skeletonizing and Analyzing Pipeline Tutorial Fits Files
<p>Fits files used in the tutorial notebooks that skeletonizes and analyzes clouds within a Cloud Factory grid. These files are the post-processed version of one grid (see Binary to Fits tutorial) with precomputed outputs of the pipeline (thresholded_data.fits and skeleton.fits). The grid is a 500x500x500 pc region of the Feedback-Dominated grid, with the total volume density of hydrogen nuclei (nhtot), volume density of carbon monoxide (nCO), molecular hydrogen (nH2), ionized hydrogen (nHP), atomic hydrogen (nH1), the gas tempearture (temp), and effective cooling from dust (tdust). </p>
EC-MS data accompanying the EC-MS quantification tutorial
<p>EC-MS data accompanying the EC-MS quantification tutorial published on ixdat/tutorials: https://github.com/ixdat/tutorials</p>
TerrSet liberaGIS Tutorial Data
<div> <p>The TerrSet software includes a comprehensive tutorial including an extensive dataset. The TerrSet tutorial is accessible from the TerrSet Help menu. The corresponding data for each tutorial can be downloaded here. You can download data for each module separately, or use the Download All button to download all of them toether. Please note that all files are zipped.</p> <p> </p> </div>
Data from: A tutorial for scanning electrochemical cell microscopy (SECCM) measurements: Step-by-Step instructions, visual resources, and guidance for first experiments
Open the record for dataset details and reuse information.
GTN Tutorial: Quality Control
<p>Data required for the Galaxy tutorial "Quality Control"</p>
Data for tutorial of RNA interactome data analysis
<p>Data required for galaxy training tutorial of RNA interactome data analysis</p>
Inputs for Galaxy tutorial on molecular docking on SARS-CoV-2 MPro
<p>Inputs for Galaxy tutorial on molecular docking on SARS-CoV-2 main protease.</p>
Tutorial videos - Using MFIT
<p>This tutorial serie is made out of four videos illustrating a complete process of using MFIT (Bodin, 2020).</p> <p>These come as additional content to the User Guide in the MFIT package</p>
Spam: Software for Practical Analysis of Materials - datasets for tutorials
<p>Datasets for <a href="https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html">spam tutorials</a>:</p> <ul> <li><strong>VEC4</strong> dataset from E.M. Charalampidou, E. Tudisco, S.A. Hall <ul> <li><a href="https://theses.fr/2011GRENI090">Experimental details available here: Charalampidou, E.M. (2011), "Experimental study of localised deformation in porous sandstones", <em>PhD Thesis</em></a></li> <li>This dataset is two x-ray tomography scans of a notched sandstone sample scanned before and after deformation in an external rig.<br> There is a rigid body displacement between the two scans that can be taken into account nicely with a registration.<br> Scans from Laboratoire 3SR, Grenoble.<br> </li> </ul> </li> <li><strong>M2EA05</strong> dataset from E. Andò, G. Viggiani and J. Andrade.<br> This data already used in the following papers for comparison to numerical simulations: <ul> <li><a href="https://doi.org/10.1016/j.jmps.2016.02.021">Kawamoto, R., Andò, E., Viggiani, G., & Andrade, J. E. (2016). Level set discrete element method for three-dimensional computations with triaxial case study. <em>Journal of the Mechanics and Physics of Solids</em>, <em>91</em>, 1-13</a></li> <li><a href="https://doi.org/10.1680/jgeot.18.T.030">Nadimi, S., Fonseca, J., Andò, E., & Viggiani, G. (2019). A micro finite-element model for soil behaviour: experimental evaluation for sand under triaxial compression. <em>Géotechnique</em>, 1-6</a></li> <li>This dataset is a series of x-ray tomographies acquired during the triaxial compression of a small sample of a "Martian Simulant" soil, performed in Laboratoire 3SR, Grenoble.<br> </li> </ul> </li> <li> <p><strong>c01_F10_b4</strong> dataset from O. Stamati, E. Roubin, E. Andò and Y. Malecot</p> <ul> <li> <p><em>This dataset belongs to a paper which is under review</em></p> </li> <li> <p>This is a 4-binned x-ray tomography of a small cylindrical sample of <em>micro-concrete</em><br> Scans from Laboratoire 3SR, Grenoble.<br> </p> </li> </ul> </li> <li> <p><strong>SandNX</strong> dataset from M. Milatz</p> <ul> <li> <p><em>The dataset is currently being analysed further</em></p> </li> <li> <p>See this publication for the experimental setup: <a href="https://doi.org/10.1007/s11440-020-00922-y">Milatz, M. (2020). An automated testing device for continuous measurement of the hysteretic water retention curve of granular media. <em>Acta Geotechnica</em>, 1-19</a><br> Data acquired on NeXT-Grenoble, a simultaneous Neutron and X-ray scanner at the ILL in Grenoble (<a href="https://dx.doi.org/10.5291/ILL-DATA.UGA-73">Experiment UGA-73</a>).<br> Neutron tomography has had a x0.7 downscale to bring it approximately in line with the pixel size for the x-ray tomography.<br> </p> </li> </ul> </li> <li> <p><strong>YehyaConcreteNX</strong> dataset from M. Yehya, A. Tengattini, E. Andò, F. Dufour</p> <ul> <li> <p><a href="https://doi.org/10.1016/j.nima.2018.02.039">Yehya, M., Ando, E., Dufour, F., & Tengattini, A. (2018). Fluid-flow measurements in low permeability media with high pressure gradients using neutron imaging: Application to concrete. <em>Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment</em>, <em>890</em>, 35-42</a></p> </li> <li> <p>Data acquired on NeXT-Grenoble, a simultaneous Neutron and X-ray scanner at the ILL in Grenoble (<a href="https://dx.doi.org/10.5291/ILL-DATA.UGA-25">Experiment UGA-25</a>).</p> </li> </ul> </li> </ul>
Fermilab LHC Physics Center Machine Learning Hands-On Advanced Tutorial Session Datasets
<p>The dataset jet_raw.tar.gz contains a sample of 2011 CMS Open Simulation in numpy arrays. The columns correspond to</p> <pre><code>['run', 'lumi', 'event', 'met', 'sumet', 'rho', 'pthat', 'mcweight', 'njet_ak7', 'jet_pt_ak7', 'jet_eta_ak7', 'jet_phi_ak7', 'jet_E_ak7', 'jet_msd_ak7', 'jet_area_ak7', 'jet_jes_ak7', 'jet_tau21_ak7', 'jet_isW_ak7', 'jet_ncand_ak7', 'ak7pfcand_ijet']</code></pre> <p>Each row is a separate anti-k<sub>T</sub> R=0.7 (AK7) jet. The code to produce the numpy arrays is located at https://doi.org/10.5281/zenodo.3901871</p> <p>The dataset jet_images.h5 contains preprocessed 2D jet images.</p> <p>The datasets ntuple_4mu_bkg.root, ntuple_4mu_gg.root, and ntuple_4mu_VV.root contain simulated LHC events with 4 muons for the background process, gluon fusion Higgs boson production, and vector boson fusion Higgs boson production.</p> <p> </p>
radio-astro-tools tutorial data
<p>These data are used in the tutorials for <a href="http://radio-astro-tools.github.io/">radio-astro-tools</a>, an organization that hosts a number of community-developed codes pertinent to the analysis of long-wavelength astronomical data in the radio, millimeter, and far-infrared regime.</p> <p> </p> <p>The current data set is a 12CO(2-1) spectral-line data cube of M33 taken with ALMA's 7-m ACA array (Project ID 2019.1.01182.S).</p>
Example BAM file for Galaxy Visualization Development Tutorial
<p>An example BAM file that can be used for the tutorial on visualization plugin development in Galaxy.</p>
rethomic tutorial data
<p>Dataset to test and learn rethomics, an R package to quantify animal behaviour (http://gilestrolab.github.io/rethomics/)</p>
Appendix for "Properties and Styles of Software Technology Tutorials"
<p>This artifact contains details of the resource collection, analysis scripts, and data analyzed in the paper "Properties and Styles of Software Technology Tutorials" by Deeksha M. Arya, Jin L.C. Guo, and Martin P. Robillard.</p>
AI4Spec Tutorial
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Tutorials of procedures intended for remote monitoring of OA
<p>Video tutorials of the procedures and technologies intended for a remonte monitoring of OA</p>
CDS input for Monocle3 tutorial - Galaxy Training Material
<p>CDS input file for Monocle3 trajectory analysis tutorial. Created from AnnData object from the upstream pre-processing.</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.