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404 results for “Reference Data”
Reference data to the low-wavenumber Raman spectral database of pharamceutical excipients
<p>Supplementary LF-785 and FT-Raman data of all the excipient samples included in the database. More information available in the following paper: <a href="https://doi.org/10.1016/j.vibspec.2020.103021">https://doi.org/10.1016/j.vibspec.2020.103021</a></p> <p>This version also contains all spectra in the .spc file format.</p>
Data for Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery
<p><strong>Description of the datasets</strong></p> <p>Data are organized as folders and compressed with tar.gz.</p> <p>There are two compressed data folder: <strong>data </strong>which used for cattle genome graphs experiment and <strong>data_human</strong> which we used for human genome graphs experiment. </p> <p><strong>Cattle genome graphs experiments</strong></p> <p>First you need to unzip the file using command <em>tar -xvzf data.tar.gz</em>. After unzipping, the data folder is organized as follows:</p> <ul> <li>Utilities: contain bovine ARS-UCD 1.2 fasta reference with the accompanying index.</li> <li>Bin: contain the softwares used in the paper (vg, liftover, vcf2diploid)</li> <li>Part1: data for analysis in variant prioritization section, further subdivided into: <ul> <li>vcf_sim: variant files from four animal in each breed used to simulate reads</li> <li>reads_sim: simulated short reads used for read mapping</li> <li>vcf_freq: variants augmented to graphs filtered based on allele frequency</li> </ul> </li> <li>Part2: data used for analysis in the section of graph mapping with breeds-filtered variants, further subdivided into: <ul> <li>vcf_breed: variant files used to graphs construction.</li> </ul> </li> <li>Part3: data used for analysis in the section of consensus genome, further subdivided into: <ul> <li>read_sims: simulated reads as in the part1, but the coordinates are liftovered to the new consensus genomes.</li> <li>reference: contain the original reference and consensus references.</li> <li>vcf_consensus: contain major allele variants to construct consensus genomes.</li> </ul> </li> <li>Part4: data analysis in the section of whole genome graph construction and variant genotyping. <ul> <li>vcf_construct: variants from chromosome 1-29 from 82 Brown Swiss used to construct BSW whole genome graph.</li> <li>BSW_graph: whole genome Brown Swiss graph with the three accompanying indexes (xg,gcsa, and gbwt).</li> </ul> </li> </ul> <p><strong>Human genome graphs experiments</strong></p> <p>First you need to unzip the <em>data_human</em> file using command <em>tar -xvzf data</em><em>_hum.tar.gz</em>. After unzipping, the data folder is organized as follows:</p> <ul> <li>reference: the g1k_v37 reference used as a graph backbone</li> <li>vcf_sim: variant files from four individuals in each population used to simulate reads</li> <li>reads_sim: simulated short reads used for read mapping</li> <li>vcf_freq: variants augmented to graphs filtered based on allele frequency</li> </ul>
The ECHAM/MESSy idealized (EMIL) model set-up: data of reference simulations
<p>This data set contains the data from simulations performed with the ECHAM/MESSy IdeaLized (EMIL) dry dynamical core model, as presented in the GMD(D) publication by Garny et al., available under doi https://doi.org/10.5194/gmd-2019-330. For details, please refer to the enclosed data description file.</p>
Reference data for MITOS2
<p>Reference data for MITOS2 derived from RefSeq63 and 81 separately for Metazoa (m), Fungi (f), and Opisthokonta (o).</p> <p>Contains</p> <p>- fasta databases for the BLAST searches</p> <p>- automatically derived covariance models for RNA searches</p> <p>- for refseq63m hidden markov models for protein prediction (http://dx.doi.org/10.1016/j.ympev.2016.09.024)</p> <p> </p>
BAM reference data: SEM raw data for the Particles Size Distribution of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a)
<p>The SEM images are given in the TIF format.</p> <p>For further information please look at:</p> <p>- Radnik, J. Kersting, R., Hagenhoff, B., Bennet, F., Ciornii, D.; Nymark, P., Grafström R. and Hodoroaba, V.- D. <em>Nanomaterials </em><strong>2021</strong>, <em>11</em>, 639. https://doi.org/10.3390/nano11030639, and</p> <p>- Vasile-Dan Hodoroaba. (2021). BAM reference data: EDS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4986420</p> <p>- Radnik, Jörg. (2021). BAM reference data: XPS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a) [Data set]. Nanomaterials. Zenodo. http://doi.org/10.5281/zenodo.4986068</p> <p>Measurement conditions:</p> <p>In the present work, a SEM of type Supra 40 (ZEISS, Oberkochen, Germany) with a Schottky field emitter and an InLens secondary electron detector was used at a 5 kV beam acceleration voltage.</p>
Coupling the COST reference plasma jet to a microfluidic device: a computational study - Figure Data
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txtools use cases omic references and processed data
<p><strong>Dataset</strong></p> <p>This dataset entry is meant to be downloaded programmatically while rendering the txtools_useCases.Rmd notebooks, to facilitate their replication using the provided genomic references. Processed data is also provided to show ready-to-use examples of data processed by txtools.</p> <p><strong>Abstract</strong></p> <p>We present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. txtools’ main inputs are BAM files and a transcriptome annotation, and the main output is a table, capturing mismatches, deletions, and the number of reads beginning and ending at each nucleotide in the transcriptomic space. txtools further facilitates downstream visualization and analyses. We showcase, using examples from the epitranscriptomic field, how a few calls to txtools functions can yield insightful and ready-to-publish results. txtools is of broad utility also in the context of structural mapping and RNA:protein interaction mapping. By providing a simple and intuitive framework, we believe that txtools will be a useful and convenient tool and pave the path for future discovery. txtools is available for installation from its GitHub repository at <a href="https://github.com/AngelCampos/txtools">https://github.com/AngelCampos/txtools</a>. </p>
BAM reference data: Temperature-dependent Young's and shear modulus data for additively and conventionally manufactured variants of Ni-based alloy Inconel IN718
<p>This BAM reference dataset reports the elastic properties (Young's modulus, shear modulus) of Ni-based alloy Inconel IN718 between room temperature and 800 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled bar). It was generated in an accredited test laboratory using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.</p>
BAM reference data: Temperature-dependent Young's and shear modulus data for additively and conventionally manufactured variants of Ti-6Al-4V
<p>This BAM reference dataset reports the elastic properties (Young's modulus, shear modulus) of titanium alloy Ti-6Al-4V between room temperature and 400 °C in an additively manufactured variant (laser-based directed energy deposition with powder as feedstock, DED-LB/M) and from a conventional process route (hot rolled bar). It was generated in an accredited test laboratory using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.</p>
BAM reference data: Temperature-dependent Young's and shear modulus data for additively and conventionally manufactured variants of austenitic stainless steel AISI 316L
<p><span>This BAM reference dataset reports the elastic properties (Young's modulus, shear modulus) of austenitic stainless steel AISI 316L between room temperature and 900 °C in an additively manufactured variant (laser powder bed fusion, PBF</span><span>‑</span><span>LB/M) and from a conventional process route (hot rolled sheet). It was generated in an accredited test laboratory using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.</span></p>
BAM Reference Data: Creep of Single-Crystal Ni-Based Superalloy CMSX-6
<p>This publication provides comprehensive metadata and test results of constant force creep tests according to <br>DIN EN ISO 204:2019-4 on the single crystal Ni-based superalloy CMSX-6 at T = 980 °C and initial stresses<br>between 140 MPa and 230 MPa. The tests were carried out in an accredited test laboratory using calibrated <br>measuring equipment. The data were audited and are BAM reference data.</p>
Reference Data for EMASE and GBRS
<p>The files in this repository support the analysis of genetically diverse samples (e.g., DO and CC mice) with Expectation-Maximization algorithm for Allele Specific Expression: <a href="https://github.com/churchill-lab/emase">EMASE</a>, and Genome reconstruction By RNA-Sequencing <a href="https://github.com/churchill-lab/GBRS">GBRS</a>, and the generation of reference files required for running these tools.</p> <p>These files are used in the The Jackson Laboratory <a href="https://github.com/TheJacksonLaboratory/cs-nf-pipelines/">Computational Sciences Nextflow pipelines</a>. Pipeline specific documentation is in the repository wiki for running <a href="https://github.com/TheJacksonLaboratory/cs-nf-pipelines/wiki/EMASE-Pipeline-ReadMe">EMASE</a> and/or <a href="https://github.com/TheJacksonLaboratory/cs-nf-pipelines/wiki/GBRS-Pipeline-ReadMe">GBRS</a>.</p>
Reference data and analysis software for "Four-color single-molecule imaging with engineered tags resolves the molecular architecture of signaling complexes in the plasma membrane"
<p>Reference data set for the single molecule co-tracking analysis presented in "Four-color single-molecule imaging with engineered tags resolves the molecular architecture of signaling complexes in the plasma membrane". Corresponding author for further inquiries:</p> <p>Prof. Dr. Jacob Piehler</p> <p>University of Osnabrück, Department of Biology/Chemistry, Division of Biophysics, Barbarastr. 11, 49076 Osnabrück, Germany</p> <p>https://www.biophysik.uni-osnabrueck.de/</p>
Data Steward Professional: Reference dataset of Data Steward related job vacancies for competences assessment
<p>Data Stewardship vacancies collection to support FAIRsFAIR Data<br> Stewardship Professional Competence Framework<br> <br> This dataset is provided to validate and support the analysis of Data<br> Stewardship competences.<br> The dataset includes a collection of vacancies from the popular job search<br> website <a href="http://indeed.com/">indeed.com</a> that responded to the search term "Data Steward".<br> <br> <strong>Acknowledgment</strong><br> The research leading to these results has received<br> funding from the Horizon2020 projects FAIRsFAIR<br> (grant number 831558)<br> <br> <strong>References</strong><br> FAIRsFAIR Project Deliverable D7.3 Data Stewardship<br> Professional Competence Framework, Work in Progress.<br> To be published Feb 2021<br> Yuri Demchenko, Lennart Stoy, Research Data Management and Data<br> Stewardship Competences in University Curriculum, In Proc. Data Science<br> Education (DSE), Special Session, EDUCON2021 – IEEE Global Engineering<br> Education Conference, 21-23 April 2021, Vienna, Austria</p>
Data for: Hematology and biochemistry of critically endangered radiated tortoises (Astrochelys radiata): reference intervals in previously confiscated subadults and variability based on common techniques
<p>Dataset for: Brenn-White M, Raphael BL, Rakotoarisoa NAT, Deem SL. 2022. Hematology and biochemistry of critically endangered radiated tortoises (<em>Astrochelys radiata</em>): reference intervals in previously confiscated subadults and variability based on common techniques. PLOS One.</p> <p>Dataset is contained in a.radiata_bloodwork.csv. Metadata and data definitions are contained in a.radiate_bloodwork_readme.txt.</p> <p>Dataset contains hematology and biochemistry values of 120 previously confiscated, clinically healthy subadult radiated tortoises living under human care within their native habitat at the Tortoise Conservation Center (TCC), Madagascar. To evaluate the effects of different commonly used techniques on these parameters, we compared results between two venipuncture sites (subcarapacial sinus and brachial vein) and three different WBC quantification methods (Natt and Herrick, Leukopet<sup>TM</sup>, and slide estimate). Data from tortoises removed from the final analyses due to sample quality issues are also included as frequency of sample quality issues varied by venipuncture site. See associated publication for detailed methods. </p> <p> </p>
Full dataset of several mechanical tests on an S355 steel sheet as reference data for digital representations
<p>The dataset provided in this repository comprises data obtained from a series of characterization tests performed to a sheet of typical S355 (material number: 1.0577) structural steel (designation of steel according to DIN EN 10025-2:2019). The tests include methods for the determination of mechanical properties such as, e.g., tensile test, Charpy test and sonic resonance test. This dataset is intended to be extended by the inclusion of data obtained from further test methods. Therefore, the entire dataset (concept DOI) comprises several parts (versions), each of which is addressed by a unique version DOI.</p> <p>The data were generated in the frame of the digitization project Innovationplatform Material<em>Digital </em>(PMD) which, amongst other activities, aims to store data in a semantically and machine understandable way. Therefore, data structuring and data formats are focused in addition to aspects in the field of material science and engineering (MSE). Hence, this data is supposed to provide reference data as basis for experimental data inclusion, conversion and structuring (data management and processing) that leads to semantical expressivity as well as for MSE experts being generally interested in the material properties and knowledge.</p>
reference data for "A Critical Comparison of Annual Glare Simulation Methods"
<p><strong>CORRECTION (20.05.2025): This repository contains a preliminary material assignment for the NMT option (in scene.tar.gz scene/options/north_metal.rad) that was not used in the final simulations. The material used in all simulations was actually:</strong></p> <p><strong>void plastic facade</strong><br><strong>0</strong><br><strong>0</strong><br><strong>5 .15 .15 .15 0.075 0.02 </strong></p> <p> </p> <p>Scene and reference results files for:</p> <p>"A Critical Comparison of Annual Glare Simulation Methods"<br>Stephen Wasilewski, Jan Wienold, Marilyne Andersen<br>2022 Buildsim Nordic, Copenhagen</p> <p>Contents:</p> <p>01-06*.tar.gz:</p> <p>reference simulation image archives, one for each of 6 scene options and view directions.<br>Simulated using Radiance rpict with the following settings:</p> <p>rpict -t 60 -vu 0 0 1 -vf VIEWFILE -x 3000 -y 3000 -dp 4096 -ar 392 -ms 0.025 -ds .2 -dt .05 -dc .75 -dr 3 -ss 16 -st .01 -ab 1 -af AMBFILE -aa .075 -ad 4096 -as 2048 -av 0.5 0.5 0.5 -lr 12 -lw 1e-5 -ab 6 -av 0 0 0 -ar 600 -ad 1500 -as 750 -dt .01 -dc 1 -ps 3 -pt .04 | pfilt -1 -e 1 -m .25 -x /3 -y /3</p> <p><br>scene.tar.gz:</p> <p>scene files including geometry, weather, materials, views and sensor points. See README.rst for details.</p> <p>reference_values.tar.gz:</p> <p>result metrics calculated on reference images in 4 ways:</p> <p>ref: using evalglare 3.02 with default values<br>refBS: using evalglare 3.02 with default values on images processed with humanblur.sh (in archive)<br>refrt: calculated numerically on pixel by pixel basis (no glare source grouping) with 2000 cd/m2 threshold<br>refrtBS: same as refRT, but solar source size is corrected accounting for point spread of typical human eye</p>
Spekboom UAV imagery and reference data
<p>Dataset and products for the publication <strong>Automated mapping of Portulacaria afra canopies for restoration monitoring with convolutional neural networks and heterogeneous unmanned aerial vehicle imagery</strong>.</p>
Text-fig. 1. Location of Wiesa fossil site in eastern Germany and other fossil sites for comparison. Explanation for map b: all fossil sites – black circles; grey circles – cities; topographic names in italics – German states (Länder). For bio- and lithostratigraphic data of fossil sites, see chapter Methodologies and material and Text-fig. 3. in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)
Text-fig. 1. Location of Wiesa fossil site in eastern Germany and other fossil sites for comparison. Explanation for map b: all fossil sites – black circles; grey circles – cities; topographic names in italics – German states (Länder). For bio- and lithostratigraphic data of fossil sites, see chapter Methodologies and material and Text-fig. 3.
Reference atmospheres, surface and instrument data used in the test experiments presented in Ridolfi et al. 2022 (doi.org/10.5194/amt-2022-82)
<p>The supplied archive includes a set of ASCII files defining the reference atmospheric and surface states that are the basis of the simulation experiments presented in the paper of Ridolfi et al. 2022 (doi.org/10.5194/amt-2022-82). Along with atmospheric and surface data, we also supply the seasonal variability and mismatch errors used in the test experiments presented in that paper, the noise error covariance matrices anticipated for FORUM and IASI-NG spectra, and some details of the retrieval setup. The archive includes a README file summarizing the contents of the various files provided.</p>
ScienceDex guides
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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.