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392 results for “tutorial”
Input for QCxMS prediction tutorial
<p>Input table for QCxMS prediction tutorial available on Galaxy Training Network. </p>
Clay tutorial videos
<p>Clay tutorial videos</p>
SCimilarity Tutorial Data
<p>SCimilarity is a unifying representation of single-cell expression profiles that quantifies similarity between expression states and generalizes to represent new studies without additional training. This enables a novel cell search capability, which sifts through millions of profiles to find cells similar to a query cell state and allows researchers to quickly and systematically leverage massive public scRNA-seq atlases to learn about a cell state of interest.</p> <p>This repository contains public datasets for SCimilarity tutorials, specifically:</p> <ol> <li>A subsample of single-cell data from Adams, et al. Science Advances, 2020 (GSE136831) as an AnnData object in h5ad format.</li> </ol> <p> </p> <p><strong>Terms of GSE136831:</strong></p> <p><em>Used with permission. Research developed by TLC4PF and the Yale School of Medicine led by Dr. Naftali Kaminski. © 2023 Pulmonary Fibrosis Cell Atlas website and associated content. All rights reserved. Please see the project website for more information: www.IPFCellAtlas.com</em></p> <p><em>In addition, please cite (https://www.science.org/doi/10.1126/sciadv.aba1983 and for a description of the website creation methodology please cite (https://doi.org/10.1152/ajplung.00451.2020).</em></p>
AnnData set for single cell analysis tutorial
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Sample datasets for E. coli C-1 genome assembly tutorial
<p>The dataset contains three files:</p> <ol> <li>Illumina_f.fq - forward reads from MiSeq run</li> <li>Illumina_r_fq - reverse reads from MiSeq run</li> <li>minion_2d.fq - Oxford Nanopore 2d reads</li> </ol> <p>Sequencing was done on genomic DNA of E. coli strain C-1 obtained from Yale Stock Center.</p>
pypsa-earth_tutorial_networks_zip
<p>unsolved and solved networks for pypsa-earth tutorial config</p>
OpenFWI Tutorial Pretrained Model and Figure
<p>OpenFWI Tutorial Pretrained Model and Figure</p>
Datasets for MuSiC Compare Tutorial
<p>These datasets are used for the MuSiC compare tutorial in Galaxy.</p>
Datasets for Deconvolution with MuSiC Tutorial
<p>These datasets are used in the MuSiC deconvolution tutorial in Galaxy. They were retrieved from the EBI's Array Express platform, originally published by:</p> <p>Segerstolpe Å, Palasantza A, Eliasson P, Andersson EM, Andréasson AC, Sun X, Picelli S, Sabirsh A, Clausen M, Bjursell MK, Smith DM, Kasper M, Ämmälä C, Sandberg R. Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes. Cell Metab. 2016 Oct 11;24(4):593-607. doi: 10.1016/j.cmet.2016.08.020. Epub 2016 Sep 22. PMID: 27667667; PMCID: PMC5069352.</p>
Datasets for MuSiC Deconvolution benchmarking tutorial suite.
<p>These are the datasets for the MuSiC deconvolution benchmarking tutorial suite.</p>
Data files for an RNA-Seq Tutorial
<p>These files go with a short transcriptomics (RNA-Seq) tutorial that I am preparing for an undergraduate level tutorial. The data analysis will be on a <a href="https://galaxyproject.org">Galaxy</a> server. I'll update the description with a link to the tutorial text when its ready.</p> <p>These data are a subset of those published by O’Connell R, Thon M et al. 2012. Lifestyle transitions in plant pathogenic <em>Colletotrichum</em> fungi defined by genome and transcriptome analyses. Nature Genetics. 44:1060–1065.</p>
solvent tutorial csc spring school 2023
<p>Input and output files tutorial solvent used in CSC spring school 26 April 2023</p>
Pretrained model for tutorial from: "PartSeg v2: Bioimage segmentation using advanced Deep Learning techniques"
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GSI Tutorial associated data
<p>This record includes the two main datasets necessary to run the GSI tutorial presented <a href="https://paocorrales.github.io/DA-documentation/content/gsi/05-tutorial.html" target="_blank" rel="noopener">here</a>:</p> <p><strong>GUESS</strong></p> <p>The 10-member ensemble background files generated using the WRF-ARW numerical model for a regional domain centered in the center and northern Argentina. For more information about the model configuration see <a href="https://doi.org/10.1016/j.atmosres.2022.106456">https://doi.org/10.1016/j.atmosres.2022.106456</a></p> <ul> <li>The 00 subfolder includes a 10-member ensemble and the ensemble mean to run the GSI system using the ENKF version. </li> <li>The 01 to 10 subfolders include the background at the analysis time and files every 10 minutes inside the assimilation window to run the GSI system using the fGAT method.</li> </ul> <p><strong>OBS</strong></p> <p>Meteorological observations in bufr format.</p> <ul> <li>cimap.20181122.t12z.01h.prepbufr.nqc is derived from a prepbufr file available at https://rda.ucar.edu/datasets/ds337.0 plus observations from private automatic meteorological weather networks in Argentina.</li> <li>abig16.20181122.t12z.bufr_d was generated using GOES-16 data available at: </li> <li>The other radiance observations comes from the Global Data Assimilation System (GDAS) Model: https://www.nco.ncep.noaa.gov/pmb/products/gfs/ <ul> <li>1bamua.20181122.t12z.bufr_d</li> <li>ssmisu.20181122.t12z.bufr_d</li> <li>1bhrs4.20181122.t12z.bufr_d</li> <li>airsev.20181122.t12z.bufr_d </li> <li>mtiasi.20181122.t12z.bufr_d</li> <li>1bmhs.20181122.t12z.bufr_d </li> <li>atms.20181122.t12z.bufr_d </li> <li>satwnd.20181122.t12z.bufr_d</li> </ul> </li> </ul>
Supplementary Materials of the Tutorial: "Promotion of Open Science in Requirements Engineering: Leveraging the ORKG and ORKG Ask for FAIR Scientific Information"
<h1>Summary</h1> <p>This collection contains all the supplementary materials of the second tutorial titled "<a href="https://conf.researchr.org/details/RE-2025/RE-2025-tutorials/1/Promotion-of-Open-Science-in-Requirements-Engineering-Leveraging-the-ORKG-and-ORKG-A" target="_blank" rel="noopener">Promotion of Open Science in Requirements Engineering: Leveraging the ORKG and ORKG Ask for FAIR Scientific Information</a>", accepted at the <a href="https://conf.researchr.org/home/RE-2025" target="_blank" rel="noopener">33rd IEEE International Requirements Engineering Conference 2025</a>.</p> <p>The materials complement the tutorial sessions and provide participants with resources to enhance their understanding and application of open science principles in the field of Requirements Engineering (RE) by leveraging the <a href="https://orkg.org/" target="_blank" rel="noopener">Open Research Knowledge Graph (ORKG)</a> and <a href="https://ask.orkg.org/" target="_blank" rel="noopener">ORKG Ask</a> for FAIR scientific information. These materials contain all the presentation slides and exercise materials so that everyone can repeat the theoretical presentations independently and carry out the practical exercises themselves at any time.</p> <h1>Contents</h1> <h2>1. Slides - All slides used in the tutorial.</h2> <table> <tbody> <tr> <td><strong>Files</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>0. RE25 Tutorial - All Sessions.pdf</td> <td>The complete set of all slides used in the tutorial, which are also provided individually for each session of the tutorial.</td> </tr> <tr> <td>1. RE25 Tutorial - Welcome.pdf</td> <td>The welcome with an overview of the content of the tutorial.</td> </tr> <tr> <td>2. RE 25 Tutorial - Introduction to Open Science in RE.pdf</td> <td>The theoretical introduction to open science regarding its importance, benefits, and incentives for researchers themselves and the wider RE community.</td> </tr> <tr> <td>3. RE25 Tutorial - Introduction to ORKG and ORKG Ask.pdf</td> <td>The theoretical introduction to the Open Research Knowledge Graph (ORKG) and ORKG Ask.</td> </tr> <tr> <td>4. RE25 Tutorial - Using SciKGTeX.pdf</td> <td>The practical exercise, with detailed step-by-step instructions on how to use the LaTeX package <a href="https://github.com/Christof93/SciKGTeX" target="_blank" rel="noopener">SciKGTeX</a> to create a FAIR-annotated publication and import it into the ORKG.</td> </tr> <tr> <td>5. RE25 Tutorial - Using the ORKG.pdf</td> <td>The practical exercise, with detailed step-by-step instructions on how to use the <a href="https://orkg.org/" target="_blank" rel="noopener">ORKG </a>to describe publications regarding their scientific information and use these descriptions to create and publish an ORKG comparison.</td> </tr> <tr> <td>6. RE25 Tutorial - Using the ORKG Ask and ORKG CSV Import.pdf</td> <td>The practical exercise, with detailed step-by-step instructions on how to use <a href="https://ask.orkg.org/" target="_blank" rel="noopener">ORKG Ask</a> and the <a href="https://orkg.org/" target="_blank" rel="noopener">ORKG</a> CSV Import to describe publications regarding their scientific information and use these descriptions to create and publish an ORKG comparison.</td> </tr> <tr> <td>7. RE25 Tutorial - Reflection and Closing.pdf</td> <td>The summary, reflection, and closing of the tutorial with an outlook to the future of <a href="https://gitlab.com/TIBHannover/orkg/ExtracTable" target="_blank" rel="noopener">ExtracTable</a>.</td> </tr> </tbody> </table> <h2>2. Exercise Materials - All exercise materials used in the tutorial.</h2> <h3>2.1 SciKGTeX Materials</h3> <table> <tbody> <tr> <td><strong>Folder</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>SciKGTeX_Example</td> <td> <p>The folder contains an example publication and all required SciKGTeX files for annotating the scientific information.</p> <p>Files:</p> <ol> <li>example.tex : LaTeX file of the example publication.</li> <li>scikgtex.lua : Required LaTeX package file for using SciKGTeX.</li> <li>scikgtex.sty : Required LaTeX package file for using SciKGTeX.</li> <li>project.zip : Zip file containing all above files for uploading as a project in Overleaf.</li> </ol> <p><em>Remark:</em> SciKGTeX is constantly being further developed. For the latest version of the required files, please refer to the corresponding <a href="https://github.com/Christof93/SciKGTeX" target="_blank" rel="noopener">GitHub project</a>.</p> </td> </tr> <tr> <td>SciKGTeX_Solution</td> <td> <p>The folder contains an Overleaf project with the solution for a possible annotation of the example publication provided.</p> <p>Files:</p> <ol> <li>example.pdf : PDF with annotations embedded into the PDF's XMP metadata.</li> <li>example.tex : LaTeX file of the example publication with annotations.</li> <li>output.xmp_metadata.xml : XMP file generated by SciKGTeX to check the annotations created.</li> <li>scikgtex.lua : Required LaTeX package file for using SciKGTeX.</li> <li>scikgtex.sty : Required LaTeX package file for using SciKGTeX.</li> <li>project.zip : Zip file containing all above files for uploading as a project in Overleaf.</li> </ol> <p><em>Remark:</em> SciKGTeX is constantly being further developed. For the latest version of the required files, please refer to the corresponding <a href="https://github.com/Christof93/SciKGTeX" target="_blank" rel="noopener">GitHub project</a>.</p> </td> </tr> </tbody> </table> <h3>2.2 ORKG Materials</h3> <table> <tbody> <tr> <td><strong>Folder</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>ORKG_Exemplary_Comparison</td> <td> <p>The folder contains a created ORKG comparison as a PDF and PNG file, consisting of 4 exemplary publications that were described with the ORKG template provided for the tutorial.</p> </td> </tr> <tr> <td>ORKG_Exemplary_Publications</td> <td> <p>The folder contains 20 PDF files with short summaries of scientific findings on empirical research practices from 20 different publications of the IEEE International Requirements Engineering Conference. The participants have received these PDFs to enter them in the ORKG and then create an ORKG Comparison.</p> <p><em>Remark:</em> We have provided the short summaries instead of the full publications to simplify the extraction process due to time constraints.</p> </td> </tr> <tr> <td>ORKG_Template</td> <td> <p>The folder contains an overview of the ORKG template used in the tutorial as a PNG file and an N3 file of its RDF structure.</p> </td> </tr> </tbody> </table> <h3>2.3 ORKG Ask & ORKG CSV Import Materials</h3> <table> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>empty_orkg_csv_file_for_orkg_csv_import.csv</td> <td> <p>The file contains an empty template for creating an ORKG CSV file for the ORKG CSV Import with own content.</p> </td> </tr> <tr> <td>empty_orkg_csv_file_for_orkg_csv_import.xlsx</td> <td> <p> </p> The file contains an empty template for creating an ORKG CSV file for the ORKG CSV Import with own content. <p> </p> </td> </tr> <tr> <td>orkg_ask_synthesized_answer_and_link_to search.txt</td> <td>The file contains the synthesized answer with references from ORKG Ask for the question "What is the state of the art in empirical research applied in requirements engineering?" with a link to the associated saved search.</td> </tr> <tr> <td>original_orkg_ask_export_for_orkg_csv_import.csv</td> <td> <p>The file contains the original content of an exported ORKG Ask result table that is revised in the tutorial to create an ORKG Comparison using the ORKG CSV Import.</p> </td> </tr> <tr> <td>original_orkg_ask_export_for_orkg_csv_import.xlsx</td> <td> <p>The file contains the original content of an exported ORKG Ask result table that is revised in the tutorial to create an ORKG Comparison using the ORKG CSV Import.</p> </td> </tr> <tr> <td>revised_orkg_ask_export_for_orkg_csv_import.csv</td> <td> <p>The file contains the revised content of an exported ORKG Ask result table that is used in the tutorial to create an ORKG Comparison using the ORKG CSV Import.</p> </td> </tr> <tr> <td>revised_orkg_ask_export_for_orkg_csv_import.xlsx</td> <td> <p>The file contains the revised content of an exported ORKG Ask result table that is used in the tutorial to create an ORKG Comparison using the ORKG CSV Import.</p> </td> </tr> </tbody> </table> <h1>Usage Notes</h1> <p>These materials are intended for use by the participants of the tutorial, the broader RE community, and everyone interested in open science. They are provided to support the long-term transition towards FAIR scientific information and to empower researchers to integrate open science infrastructures into their work.</p> <h1>License</h1> <p>The materials are released under <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" rel="noopener">Creative Commons Attribution 4.0 International (CC BY 4.0) license</a>, allowing for reuse and distribution in accordance with open science practices.</p>
Data from: Simplified models of the symmetric single-pass parallel-plate counterflow heat exchanger: a tutorial
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SICSS - Tutorial Dataset File
<p>Code for analyzing this data <a href="https://github.com/virallab/SICSS_Tutorial">https://github.com/virallab/SICSS_Tutorial</a></p>
FITS data file for Learn Astropy Celestial Coords #1 tutorial
<p>This is for hosting the fits data file of the planetary nebula NGC 7293 for use in the Learn Astropy Celestial Coords #1 tutorial. </p>
Training material for Galaxy 101 tutorial
<p>The data provided here are part of a Galaxy tutorial "Galaxy 101". The files contain BED-formatted 1) coding exons on chromosome 22 of human genome version hg38, 2) SNPs from dbSNP version 153 located in whole genes, and 3) repeats from hg38 chr22.</p>
Mock datasets for MPoL tutorials and tests
<p>`*.npz` and `*.asdf` files containing visibilities are in the TMS format (opposite that of CASA).</p><p>logo_cube.noise.npz visibilities have been rescaled such that data - model / sigma follows the expected Gaussian envelope.</p><p>HD 143006 continuum visibilities have flagged outliers removed and weights rescaled such that the data - model / sigma follows the expected Gaussian envelope, for each spectral window.</p><p>AS 209 continuum visibilities have been averaged across frequency and have their weights rescaled such that the data - model / sigma follows the expected Gaussian envelope, for each spectral window.</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.