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3,172 results for “Publications”
S44 | STATINS | Statins Collection from Public Resources
<p>This is the collection associated with list S44 STATINS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S44</p> <p>STATINS</p> <p><strong>S</strong><strong>tatins Collection from Public Resources</strong></p> <p>STATINS <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/120219Update/STATINS_14022019.xlsx">XLSX</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/120219Update/STATINS_14022019.csv">CSV</a> (14/02/2019)<br> CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/statins">STATINS List</a></p> <p>STATINS <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/120219Update/STATINS_InChIKeys_14022019.txt">InChIKeys</a> (14/02/2019)</p> <p>A list of statins (lipid-lowering medications) compiled from public resources, details on CompTox. </p>
Metabarcoding reveals a high diversity of woody host-associated Phytophthora spp. in soils at public gardens and amenity woodlands in Britain
<p>This is the demultiplexed Illumina MiSeq raw sequencing data from two 96-well plates from the following recent publication, shared with permission of the corresponding author, Sarah Green:</p> <p>Riddell <em>et al.</em> (2019). Metabarcoding reveals a high diversity of woody host-associated <em>Phytophthora</em> spp. in soils at public gardens and amenity woodlands in Britain. https://doi.org/10.7717/peerj.6931<br> <br> It consists of 244 gzipped compressed plain text FASTQ format sequence files, grouped into 122 pairs by the widely used R1 and R2 suffix. The files have been renamed to use the anonymised site numbers (1 to 14) as in the paper, see also supplementary table one for site metadata. Additionally there are two negative controls, and positive control DNA mixtures of 10 and 15 species as described in the paper.<br> </p>
Modelling of ready biodegradability based on combined public and industrial data sources
<p>The European REACH (Registration, Evaluation, Authorization and restriction of Chemicals) Regulation, requires marketed chemicals to be evaluated for Ready Biodegradability (RB). In-silico prediction is a valid alternative to expensive and time-consuming experimental testing. However, currently available models may not be relevant to predict compounds of industrial interest, due to accuracy and applicability domain restriction issues.</p> <p>In this work we present a new and extended RB dataset (2830 compounds), issued by the merging of several public data sources. It was used to train classification models, which were externally validated and benchmarked against already-existing tools on a set of 316 compounds coming from the industrial context. New models showed good performances in terms of predictive power (BA = 0.74 – 0.79) and data coverage (83 – 91 %).</p> <p>The Generative Topographic Mapping approach was employed to compare the chemical space of the various data sources: several chemotypes and structural motifs unique to the industrial dataset were identified, highlighting for which chemical classes currently available models may have less reliable predictions.</p> <p>Finally, public and industrial data were merged into Global dataset containing 3146 compounds and including a significant subset of compounds coming from the industrial context. This is the biggest dataset reported in the literature so far which covers some chemotypes absent in the public data. Thus, predictive model developed on the Global dataset has much larger applicability domain than related models built on publicly available data. The developed model is available for the user on the Laboratory of Chemoinformatics website.</p> <p>This dataset is only the "All-Public" set, since the industrial compounds cannot be disclosed.</p> <p>This update contains additional entries from [J. Chem. Inf. Model. 52 (2012), pp. 655–669] and [J. Chem. Inf. Model. 53 (2013), pp. 867–878]</p>
Dataset related to the publication "Lasing in an Assembled Array of Silver Nanocubes"
<p>This archive contains the raw data used to draw the graphs published in the paper "Lasing in an Assembled Array of Silver Nanocubes". </p>
Dataset for the publication "Implementation of an exact completing method of generation for face-milled spiral bevel gears with uniform depth taper"
<p>This dataset contains geometric and graphics data associated with the referenced paper, enabling the reproduction of the conducted research. </p>
Public attributions made on Bionomia, December 2022
<p>Public attributions of natural history specimens made for collectors and determiners on Bionomia (<a href="https://bionomia.net/">https://bionomia.net</a>) using data from the Global Biodiversity Information Facility, <a href="https://gbif.org/">https://gbif.org</a>. This file was downloaded from the website on the 28 December 2022. More recent versions of the resource can be found on the official repository on Zenodo for Bionomia at <a href="https://doi.org/10.5281/zenodo.13937806" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13937806</a> .</p> <p>Each row of the file has a subject, predicate and object...</p> <ul> <li>Subject is the specimen identifer from the Global Biodiversity Information Facility e.g. https://gbif.org/occurrence/1801358422</li> <li>Predicate is the indicator as to whether the action of the person is as an identifier or collector. e.g. http://rs.tdwg.org/dwc/iri/identifiedBy</li> <li>Object Is the attributed preson identifed by their ORCID identifier, or Wikidata identifier. e.g. https://orcid.org/0000-0001-9008-0611</li> </ul>
Data associated with following publication: "In situ optical sub-wavelength thickness control of porous anodic aluminum oxide"
<p>Data associated with following publication: "In situ optical sub-wavelength thickness control of porous anodic aluminum oxide" (DOI: <a href="https://doi.org/10.3762/bjnano.15.12" target="_blank" rel="noopener">https://doi.org/10.3762/bjnano.15.12</a>)</p>
Data for the publication: Recombinant silk protein condensates show widely different properties depending on the sample background
<p>This entry includes raw data for the publication "Recombinant silk protein condensates show widely different properties depending on the sample background". The original publication was published in: Journal of Materials Chemistry B, DOI: 10.1039/d4tb01422g</p> <p>The folder "Videos_Micropipette_Aspiration_Zenodo.zip" contains 9 TIF files, labeled Number1 - Number9. The numbering corresponds to the numbering of IMAC condensates studied with micropipette aspiration in the publication. Each TIF file is an image stack from a time series.</p> <p>The folders "Videos_IMAC_silk_with_BG_lysate_coalescence.zip", "Videos_HT_silk_coalescence.zip", and "Videos_IMAC_silk_coalescence.zip" all contain subfolders labeled with the purification method, the framerate of the videos and then consecutive numbering. Each of these folders contains the frames of the video as single TIF files.</p> <p>Please find more information in the read_me file uploaded.</p>
TDA4ContextualEmbeddings - Public - Debug Data for the codebase of the publication "Local Topology Measures of Contextual Language Model Latent Spaces With Applications to Dialogue Term Extraction"
<p>Debug dataset for testing the <a href="https://gitlab.cs.uni-duesseldorf.de/general/dsml/tda4contextualembeddings-public">codebase</a> of the paper <a href="https://doi.org/10.18653/v1/2024.sigdial-1.31">“Local Topology Measures of Contextual Language Model Latent Spaces With Applications to Dialogue Term Extraction”</a> published at the 25th Meeting of the Special Interest Group on Discourse and Dialogue, Kyoto, Japan (SIGDIAL 2024).</p>
Supplementary dataset to publication: Oxford nanopore technologies - a valuable tool to generate whole-genome sequencing data for in silico serotyping and the detection of genetic markers in Salmonella, Thomas et al 2023
<p>Bacteria of the genus <em>Salmonella</em> pose a major risk to livestock, the food economy, and public health. <em>Salmonella</em> infections are one of the leading causes of food poisoning. The identification of serovars of <em>Salmonella</em> achieved by their diverse surface antigens is essential to gain information on their epidemiological context. Traditionally, slide agglutination has been used for serotyping. In recent years, whole-genome sequencing (WGS) followed by <em>in silico</em> serotyping has been established as an alternative method for serotyping and the detection of genetic markers for <em>Salmonella</em>. Until now, WGS data generated with Illumina sequencing are used to validate <em>in silico</em> serotyping methods. Oxford Nanopore Technologies (ONT) opens the possibility to sequence ultra-long reads and has frequently been used for bacterial sequencing. In this study, ONT sequencing data of 28 <em>Salmonella</em> strains of different serovars with epidemiological relevance in humans, food, and animals were taken to investigate the performance of the <em>in silico</em> serotyping tools SISTR and SeqSero2 compared to traditional slide agglutination tests. Moreover, the detection of genetic markers for resistance against antimicrobial agents, virulence, and plasmids was studied by comparing WGS data based on ONT with WGS data based on Illumina. Based on the ONT data from flow cell version R9.4.1, <em>in silico</em> serotyping achieved an accuracy of 96.4 and 92% for the tools SISTR and SeqSero2, respectively. Highly similar sets of genetic markers comparing both sequencing technologies were identified. Taking the ongoing improvement of basecalling and flow cells into account, ONT data can be used for <em>Salmonella in silico</em> serotyping and genetic marker detection.</p>
Graphic Illustration of Workshop Discussion Synthesis: A Public Health Perspective
<p><a href="https://lib.ku.edu/people/courtney-foat" target="_blank" rel="noopener">Courtney Foat</a>, Advisor for Strategic Initiatives & Organizational Engagement at the University of Kansas, graphically recorded and synthesized the key public health themes from our participant discussion session at an NSF-supported Workshop: Digital Collections Data and Tracking Disease.</p>
Dataset used in the publication entitled "Decomposition by Approximation with Pulse Waves Allowing Further Research on Sources of Voltage Fluctuations"
<p>Dataset obtained from experimental research carried out in the prepared laboratory setup. Based on the dataset, the proposed new decomposition method by approximation with pulse waves has been validated in the publication: Kuwałek P., Decomposition by Approximation with Pulse Waves Allowing Further Research on Sources of Voltage Fluctuations. The description of the prepared laboratory setup is presented in this publication. The research results are part of the work under the project entitled "Voltage fluctuation diagnostic focused on identification and localization disturbing loads in power grids" funded by the National Science Centre, Poland - 2021/41/N/ST7/00397.</p>
Supplementary Material to the Publication Genotyping of Francisella tularensis subsp. holarctica from Hares in Germany
<p>Supplementary Material in Open Data Format to Publication Genotyping of Francisella tularensis subsp. holarctica from Hares in Germany</p>
Data on public understandings of and attitudes towards carbon-smart urban green infrastructure in Kumpula, Helsinki
<p>A public participatory GIS -survey dataset detailing public understandings of and attitudes towards carbon-smart urban green infrastructure in Kumpula, Helsinki, Finland.</p>
South African Public Protector Investigate Reports Data
<p>Please read the Code Book.</p> <p>Author: Tomohiro Hosoi</p> <p> </p> <p><strong>Aim of the Data Set</strong></p> <p>The South African Public Protector Investigate Reports Data is the original data constructed by Tomohiro Hosoi (“the author”), who aims to investigate the role of the Public Protector in South Africa. His research article titled “South African Public Protector: People’s Watchdog or Politicians’ Lapdog?” which is published in <em>African Study Monographs </em>2023, uses this data set.</p> <p>The author aims to share the dataset for researchers to more sophisticated research in the future. The author provides the data in both excel and CSV format.</p> <p> </p> <p><strong>Source of the Data</strong></p> <p>The author downloaded all of the Investigation Reports on the Office of Public Protector’s Home Page on 15 April 2022. (<a href="http://www.publicprotector.org/?q=content/investigation-reports-categories">http://www.publicprotector.org/?q=content/investigation-reports-categories</a>). The data includes 388 reports from 2008 to 2022. The author reads all of the reports and codes the information containing them.</p>
Supplementary dataset to publication: "Genomic epidemiology of Campylobacter fetus subsp. venerealis from Germany"
<p>Supplementary dataset to publication: "Genomic epidemiology of Campylobacter fetus subsp. venerealis from Germany" by Abdel-Glil Mostafa Y., Hotzel Helmut, Tomaso Herbert, Didelot Xavier, Brandt Christian, Seyboldt Christian, Linde Jörg, Schwarz Stefan, Neubauer Heinrich, El-Adawy Hosny. Genomic epidemiology of Campylobacter fetus subsp. venerealis from Germany. Frontiers in Veterinary Science. volume 9 (https://www.frontiersin.org/articles/10.3389/fvets.2022.1069062) <br> </p>
Data set for publication: Determination of Virulence-Associated Genes and Antimicrobial Resistance Profiles in Brucella Isolates Recovered from Humans and Animals in Iran Using NGS Technology
<p>This dataset includes information on resistance profiling, as well as antimicrobial resistance (AMR) genes and virulence-related factors that were identified in <em>Brucella</em> isolates recovered from humans and animals in different regions of Iran using classical phenotyping and next-generation sequencing (NGS) technology.</p>
Supplementary dataset to publication: "Elevated platforms with integrated weighing beams allow automatic monitoring of usage and activity in broiler chickens"
<p>The dataset supplements the journal article "Elevated platforms with integrated weighing beams allow automatic monitoring of usage and activity in broiler chickens" by H. Schomburg, J. Malchow, O. Sanders, J. Knöll and L. Schrader, that appeared in Smart Agricultural Technology 3 (2023), https://doi.org/10.1016/j.atech.2022.100095. The file archives trial1.zip and trial2.zip contain csv files with platform weighing system data measured from June 19, 2019 to July 22, 2019 (trial 1) and from September 9, 2019 to October 14, 2019 (trial 2) in a broiler chicken barn at Friedrich-Loeffler-Institut, Institute of Animal Welfare and Animal Husbandry, Celle. A detailed description of data structure is given in 00_hl_weighing_system_data_overview.txt.</p>
Dataset regarding the « Reasons for concern » about climate change from figures in IPCC and related publications
<p>This data corresponds to the 'burning ember' diagrams from IPCC reports and related publications (IPCC TAR, Smith et al. 2009 for AR4-related embers, AR5 and SR15). It was used to build figure 3 of Zommers et al. 2020 (<em>Burning Embers: Towards more transparent and robust climate change risk assessments</em>. Accepted for publication in Nature Reviews Earth & Environment). The data provided here is the result of extraction of information from the original figures, as presented in the related technical document <a href="https://doi.org/10.5281/zenodo.3992856">10.5281/zenodo.3992856</a>. As explained in the Supplementary Information of Zommers et al. 2020 and the technical document, this is not data from the IPCC. The provided values are approximations of the global mean temperature increase corresponding to each change in risk in the original diagrams. The rigour of the preparation process and the limitations of the dataset are explained in the technical document.</p>
nanoindentation data associated with the publication "On the elastic microstructure of bulk metallic glasses" in Materials&Design 2023
<p>This dataset consists of indentation data measured with a conospherical tip in a Hysitron-Bruker TI980 Nanoindenter on the surface of a <100> Silicon wafer and a polished cross-sectional cut of a Zr65Cu25Al10 bulk metallic glass.</p> <p>It is associated with the following publication: <br>Birte Riechers, Catherine Ott, Saurabh Mohan Das, Christian H. Liebscher, Konrad Samwer, Peter M. Derlet and Robert Maass "On the elastic microstructure of bulk metallic glasses" Materials and Design 229, (2023) 111929. https://doi.org/10.1016/j.matdes.2023.111929</p> <p>All experimental information can be found in this paper and in the accompanying supplementary information.</p> <p>This electronic version of the data was published on the "Zenodo Data repository" found at http://zenodo.org/deposit in the community "Bundesanstalt fuer Materialforschung und -pruefung (BAM)".</p> <p>The authors have copyright to these data. You are welcome to use the data for further analysis, but are requested to cite the original publication whenever use is made of the data in publications, presentations, etc. </p> <p>Any questions regarding the data can be addressed to birte.riechers@bam.de who would also appreciate a note if you find the data useful.</p> <p>____________________________________________________________________</p> <p>The data format is defined as described below:</p> <p>In total, Fifteen text files exist that result in five different data sets.</p> <p>Two data sets represent measurements on Silicon, these are specifically the topography (mapped height profile) and indentation modulus (Si-topography.txt and Si-modulus.txt). The connected lateral information of these mapped quantities (i.e. Si-X_topography.txt and Si-Y_topography.txt; Si-X_modulus.txt and Si-Y_modulus.txt). This amounts to six .txt files connected to measurements on Silicon.</p> <p>Three data sets represent measurements on the Zr65Cu25Al10 bulk metallic glass. These are specifically the topography (MG-topography.txt), the indentation modulus (MG-modulus.txt), and the curvature-corrected indentation modulus (MG-curvcorr_modulus.txt). The connected lateral information of these mapped quantities (i.e. MG-X_topography.txt and MG-Y_topography.txt; MG-X_modulus.txt and MG-Y_modulus.txt; MG-X_curvcorr-modulus.txt and MG-Y_curvcorr-modulus.txt). This amounts to nine .txt files connected to measurements on the metallic glass.</p> <p>The files are plain text files with the data points separated by commata. Topography data is stated in units of Nanometer, modulus data is stated relative to its mean as unit-less values.</p> <p>Beside the .txt files, one figure (.pdf) with a plot of each data set is provided for reference, and the python code (Riechers_OnTheElasticMicrostructureOfBulkMetallicGlasses_zenodo.ipynb) generating these figures from the data sets is uploaded to this repository as well.</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.