Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,101
datasets available to search
ShareScore release 0.9.0
Dataset results
3,101 results for “tables”
Figure 3 in Development, reproduction and life table parameters of Tetranychus turkestani (Acari: Tetranychidae) on three different host plants
Figure 3 Age-stage-specific life expectancy (exj) of Tetranychus turkestani on: a. cowpea, b. white bean, c. red bean.
Figure 2 in Development, reproduction and life table parameters of Tetranychus turkestani (Acari: Tetranychidae) on three different host plants
Figure 2 Age-specific survival rate (lx), fecundity (mx) and maternity l (x mx) of Tetranychus turkestani on: a. cowpea, b. white bean, c. red bean.
Figure 1 in Development, reproduction and life table parameters of Tetranychus turkestani (Acari: Tetranychidae) on three different host plants
Figure 1 Age-stage-specific survival rate (Sxj) of Tetranychus turkestani on: a. cowpea, b. white bean, c. red bean.
Figure 4 in Development, reproduction and life table parameters of Tetranychus turkestani (Acari: Tetranychidae) on three different host plants
Figure 4 Age-stage-specific life expectancy (vxj) of Tetranychus turkestani on: a. cowpea, b. white bean, c. red bean.
Early 3D Evolution of the SARS-CoV-2 proteome -- Supplementary Tables and Models
<p><strong>Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic</strong></p> <p><a href="https://iqb.rutgers.edu/covid-19_proteome_evolution">https://iqb.rutgers.edu/covid-19_proteome_evolution</a></p> <p> </p> <p><strong>Legends for Supplementary Figures for 29 </strong><strong>SARS-CoV-2 Study Proteins</strong></p> <p><strong>Separate analysis of protein changes was performed for each study protein and complex. Description below applies to all figures.</strong></p> <p><strong>A</strong>: Observed frequencies for all USV substitutions of Native Residue (i.e., amino acid type in the reference protein sequence) changing to Substituted Residue for a given protein/complex. Red boxes enclose conservative substitutions for hydrophobic, uncharged polar, positively charged, and negatively charged amino acids, respectively in order from upper left to lower right. Cysteine, Glycine and Proline are excluded from these groupings.</p> <p><strong>B-D</strong>: Normalized Frequency histograms for ΔΔG<sup>App</sup> calculated for all USVs for a given protein/complex. These were calculated using three methods, which we refer to as hard-hard (B), soft-hard (C), and soft-soft (D), based on the scoring functions used for sidechain rotamer optimization and gradient-based energy minimization respectively (see methods). All energy values described in the text were obtained using the soft-hard method. Overlay of energy histogram with fitted bi-Gaussian curve (solid red line) and fitted single Gaussian curves for subsets of USVs with surface (green), boundary layer (yellow), or core (blue) substitutions. USVs with multiple substitutions were included in single Gaussian fitting when all substitutions mapped to the same region of the study protein. The data used for fitting includes the energies of all unique protein models produced by a given method, excluding extreme outliers with energy values greater than 3 standard deviations away from the central mean.</p> <p><strong>E-G</strong>: USV Count histograms indicate the number of USVs among the full set for a given protein in which each site included a substitution. Sites are separated by burial layer. Substitutions at sites that are absent from the available crystal structures are excluded from the histograms. In most cases, only a single protein is analyzed, and only panel E is included. In the case of complexes, a separate histogram is provided for each protein in the complex: for methyltransferase nsp10-nsp16, E is nsp10 and F is nsp16; for RDRP nsp12-nsp7-nsp8, E is nsp7, F is nsp8, and G is nsp12.</p> <p> </p> <p><strong>Legends for Supplementary Tables for 29 </strong><strong>SARS-CoV-2 Study Proteins</strong></p> <p><strong>Table: USVs</strong>: All identified USVs for a protein/complex. Columns are:</p> <ul> <li>date: Date of first collection of a strain with the USV reported to GISAID</li> <li>gisaid_count: The number of sequences in the GISAID database that include the USV</li> <li>id: The GISAID strain identification for the first collected instance of the USV</li> <li>location: The country in which the first strain including the USV was collected</li> <li>substitutions: All substitutions in the USV, in the form [chain]_[sequence][site][substitution], with multiple substitutions separated by semicolons</li> <li>is_in_PDB: whether a substitution is present in the PDB model used to generate the USV structure, with multiple substitutions separated by semicolons</li> <li>multiple: whether more than one amino acid substitution is present in the USV</li> <li>conservative: whether a substitution is conservative, with multiple substitutions separated by semicolons</li> <li>layer: Identification of the burial layer (surface, boundary, or core) of a substitution in the reference structure, with multiple substitutions separated by semicolons and substitutions absent from the PDB excluded</li> <li>sh_rmsd: The RMSD of the USV to the reference structure when modeled using the soft-hard method</li> <li>sh_ddG: The ΔΔG<sup>App</sup> of the USV when modeled using the soft-hard method</li> <li>hh_rmsd: The RMSD of the USV to the reference structure when modeled using the hard-hard method</li> <li>hh_ddG: The ΔΔG<sup>App</sup> of the USV when modeled using the hard-hard method</li> <li>ss_rmsd: The RMSD of the USV to the reference structure when modeled using the soft-soft method</li> <li>ss_ddG: The ΔΔG<sup>App</sup> of the USV when modeled using the soft-soft method</li> </ul> <p> </p> <p><strong>Table: Substitutions</strong>: All substitutions identified for a protein/complex</p> <ul> <li>chain: The chain identifier of the protein in the PDB file in which the substitution is present</li> <li>site: The residue number at which the substitution is present</li> <li>reference: The one-letter amino acid name of the residue in the reference sequence</li> <li>mutant: The one-letter amino acid name of the residue in a USV</li> <li>conservative: Indication of whether a substitution is conservative</li> <li>in_pdb: whether the substitution site is present in the PDB model used to generate the USV structure</li> <li>layer: Identification of the burial layer (surface, boundary, or core) of a substitution in the reference structure</li> <li>date: date: Date of first collection of a strain with the substitution reported to GISAID</li> <li>location: The country in which the first strain including the substitution was collected</li> <li>gisaid_count: The number of sequences in the GISAID database including the substitution</li> <li>usv_count: The number of identified USVs including the substitution</li> <li>ddG: The soft-hard ΔΔG<sup>App</sup> of the USV that includes only the substitution, left empty if no single-substitution USV was identified with the substitution</li> <li>single: Indication of whether the substitution was present in a single-substitution USV</li> <li>multiple: Indication of whether the substitution was present in a USV with multiple substitutions</li> <li>associates: List of all other substitutions that were identified in a USV that included the substitution</li> <li>strains: List of all USV-representative GISAID strains that included the substitution, with the single-substitution USV strain listed first if one was available</li> </ul> <p> </p> <p><strong>Table: Gaussian Fit Statistics</strong>: Fitted models for the energies of all USVs either together (ALL) or by study protein.</p> <ul> <li>fit: The number of Gaussian curves in the fitted energy model </li> <li>protein: The protein/complex name</li> <li>method: The modeling method used to calculate energy values</li> <li>layer: The subset burial layer (surface, boundary, or core) of USVs for which the energy model was fitted, excluding all USVs with substitutions not in that layer</li> <li>μ<sub>1</sub>: Mean of the first Gaussian in the fitted model</li> <li>σ<sub>1</sub>: Variance of the first Gaussian in the fitted model</li> <li>wt<sub>1</sub>: Weight of the first Gaussian in the fitted model</li> <li>μ<sub>2</sub>: Mean of the second Gaussian in the fitted model</li> <li>σ<sub>2</sub>: Variance of the second Gaussian in the fitted model</li> <li>wt<sub>2</sub>: Weight of the second Gaussian in the fitted model</li> <li>R<sup>2</sup>: R-squared value indicating the goodness of fit</li> </ul> <p> </p> <p><strong>Description of Computed Structural Models </strong><strong>for Unique Sequence Variants for 29 </strong><strong>SARS-CoV-2 Study Proteins.</strong></p> <p><strong>USV Computed Structural Models</strong>. Computed structural models for all amino acid substituted USVs. We are providing the structural models of all study proteins modeled using the soft-hard modeling method (see Methods). Structural models are named according to the GISAID strain identification of the first strain in which the USV was identified, followed by an underscore-separated list of substitutions in the form [chain]_[sequence][site][substitution]. Atomic coordinates for each computed structural model are provided in the legacy Protein Data Bank format used by most molecular graphics software tools (see <a href="https://www.wwpdb.org/documentation/file-format-content/format33/v3.3.html">https://www.wwpdb.org/documentation/file-format-content/format33/v3.3.html</a> for detailed description).</p>
Loire & Galtier 2021 Peer Community Journal Supplementary Table S1
<p>This table shows the analyzed species and species pairs and estimated of synonymous heterozygosity (piS) and inbreeding coefficient (F)</p>
Tara Oceans (2009-2013) rDNA 18S V9 ASV table (DADA2) with nf-core/ampliseq
<p>This repository contains datasets describing the DADA2 ASVs generated from <em>Tara</em> Oceans 18S V9 rDNA data. The ASVs were generated using the nf-core workflow <a href="https://nf-co.re/ampliseq" target="_blank" rel="noopener">ampliseq</a>. Please refer to the readme file (README.html) for more details.</p>
Tara Oceans (2009-2013) rDNA 18S V4 ASV table (DADA2) with nf-core/ampliseq
<p>This repository contains datasets describing the DADA2 ASVs generated from <em>Tara</em> Oceans 18S V4 rDNA data. The ASVs were generated using the nf-core workflow <a href="https://nf-co.re/ampliseq" target="_blank" rel="noopener">ampliseq</a>. Please refer to the readme file (README.html) for more details.</p>
OTU table of genus from Tibet WWTPs
<p>Activated sludge was collected from two municipal wastewater treatment plants (WWTPs) located in a high altitude Plateau in Tibet, China (~3650 m above the sea level). T1 is applied for cyclic activated sludge system (CASS), while T2 is operated at anaerobic-anoxic-aerobic (A2O) process. DNA samples were taken from bioreactor of T1, aerobic and anaerobic bioreactors of T2 (marked as T2AE and T2AN). The 16S rRNA gene amplicons of V4-V5 regions that were sequenced on an Illumina HiSeq PE250 platform, and then annotated using the 16S-Silva database. Data present here are normalized OTU relative number of each sample are presented at the taxonomic levels of genus.</p>
Online Supplemental Tables - An atlas of genome-wide gene expression and metabolite associations and possible mediation effects towards body mass index
<p>Summary statistics of metabolite-gene expression associations and mediation analyses of effects on body mass index.</p> <p>The corresponding publication is currently under revision.</p> <ul> <li><strong>Online Supplemental Table 1</strong>: Gene expression-metabolite association summary statistics from 97 metabolites and metabolite ratios and up to 15175 genes calculated seperately in the LIFE-Adult, LIFE-Heart, LIFE-AMI and the Sorb studies. Associations were adjusted for six covariates.</li> <li><strong>Online Supplemental Table 2</strong>: Random-effects meta-analyzed gene expression-metabolite association summary statistics. P-Values were adjusted for multiple testing using a hierarchical adjustment procedure both on local (within phenotypes) and on global (across phenotypes) level.</li> <li><strong>Online Supplemental Table 3</strong>: Single-study association results needed for checking mediation analysis assumptions and for calculating mediation statistics. Only gene expression probe-metabolite pairs that associated significantly at hierarchical FDR=5% in the gene-expression-metabolite association meta-analysis qualified for these associations.The following Associations were tested: gene expression probes ~ metabolites, log-BMI ~ metabolites log-BMI ~ gene expression, log-BMI ~ gene expression + metabolite. Associations were adjusted for six covariates. P-values</li> <li><strong>Online Supplemental Table 4</strong>: Meta-analyzed association results needed for checking mediation analysis assumptions and for calculation mediation statistics.</li> <li><strong>Online Supplemental Table 5: </strong>Mediation analysis summary statistics. Mediations of gene expression effects (exposure) via metabolite effects (mediatior) and of metabolite effects (exposure) via gene expression effects (mediator) on body mass index (outcome) were tested.</li> </ul> <p> </p>
Supplemental Data and Code for "An exact version of Life Table Response Experiment analysis, and the R package exactLTRE"
<p>This dataset enables the user to repeat the analyses presented in the manuscript "An exact version of Life Table Response Experiment analysis, and the R package exactLTRE." It is comprised of two compressed archives: one which contains code, and one which contains data.</p>
Table S1 - Economic Costs of Protecting Islands from Invasive Alien Species
<p>Dataset analysed in relation to the paper 'Economic Costs of Protecting Islands from Invasive Alien Species' published in Conservation Biology in 2022</p>
PID table for the articles of the "Dialektikê. Cahiers de typologie analytique" journal
<p>This table contains the different persistent identifier (PID) related to the digital version of the articles of the <em>Dialektikê. Cahiers de typologie analytique</em> journal of archaeology (ISSN 1147-114X and 1169-0046). These articles are referenced by multiple services:</p> <ul> <li><em>HAL</em> <em>– Hyper Articles en Ligne </em>(<a href="https://hal.archives-ouvertes.fr/search/index/?qa[journalTitle_t][]=%22Cahiers+de+typologie%22">https://hal.archives-ouvertes.fr</a>).</li> <li>The <em>Lithic Types</em> blog (<a href="https://lithictypes.hypotheses.org/">https://lithictypes.hypotheses.org</a>).</li> <li><em>Isidore</em> (<a href="https://isidore.science">https://isidore.science</a>).</li> <li><em>Worldcat</em> (<a href="https://www.worldcat.org)">https://www.worldcat.org)</a>.</li> <li><em>FRANTIQ</em> (<a href="https://catalogue.frantiq.fr">https://catalogue.frantiq.fr</a>)</li> </ul> <p>Each row of the table corresponds to an article and present the following data:</p> <ul> <li><strong>authors</strong>: authors of the article.</li> <li><strong>year</strong>: publication year of the article.</li> <li><strong>doi</strong>: doi of the digital version of the article stored in <em>Zenodo</em>.</li> <li><strong>hdl-hypotheses</strong>: <em>Isidore </em>handle of the reference to the article on the <em>Lithic types</em> blog.</li> <li><strong>oclc-hypotheses</strong>: OCLC unique identifier of the reference to the article on the <em>Lithic types</em> blog.</li> <li><strong>hal</strong>: HAL unique identifier to the reference to the article.</li> <li><strong>hdl-hal</strong>: <em>Isidore</em> handle of the reference to the article in <em>HAL</em>.</li> <li><strong>ark-frantiq</strong>: ark of the reference to the article in <em>FRANTIQ</em>.</li> </ul>
CO1 Sequences and Material Table of Western Palearctic Weevil Taxa
<p>The ZIP file contains the CO1 sequence dataset and its corresponding material table from the research article:<br> Schütte A, Stüben PE, Astrin JJ (2023) Molecular Weevil Identification Project: A Thoroughly Curated Barcode Release of 1300 Western Palearctic Weevil Species (Coleoptera: Curculionoidea) - <em>Biodiversity Data Journal</em> <strong>11</strong>.</p>
M. Kelly PhD thesis; Chapter 2 - Supplemental Table S1
<p>Supplemental Table for my PhD thesis (Chapter 2). Supplemental Table S1 contains the sample data for all specimens used in this study.</p>
M. Kelly PhD thesis; Chapter 3 - Supplemental Table S1
<p>Supplemental Table for my PhD thesis (Chapter 3). Supplemental Table S1 contains all collection and processing data for the specimens used in this study.</p>
M. Kelly PhD thesis; Chapter 2 - Supplemental Table S2
<p>Supplemental Table for my PhD thesis (Chapter 2). Supplemental Table S2 contains the biometric data for all specimens used in this study.</p>
PLBD (Protein Ligand Binding Database) table description XML file
<p>PLBD (Protein Ligand Binding Database) table description XML file<br> =================================================================</p> <p>General<br> -------</p> <p>The provided ZIP archive contains an XML file "main-database-description.xml" with the description of all tables (VIEWS) that are exposed publicly at the PLBD server (https://plbd.org/). In the XML file, all columns of the visible tables are described, specifying their SQL types, measurement units, semantics, calculation formulae, SQL statements that can be used to generate values in these columns, and publications of the formulae derivations.</p> <p>The XML file conforms to the published XSD schema created for descriptions of relational databases for specifications of scientific measurement data. The XSD schema ("relational-database_v2.0.0-rc.18.xsd") and all included sub-schemas are provided in the same archive for convenience. All XSD schemas are validated against the "XMLSchema.xsd" schema from the W3C consortium.</p> <p>The ZIP file contains the excerpt from the files hosted in the https://plbd.org/ at the moment of submission of the PLBD database in the Scientific Data journal, and is provided to conform the journal policies. The current data and schemas should be fetched from the published URIs:</p> <p> https://plbd.org/<br> https://plbd.org/doc/db/schemas<br> https://plbd.org/doc/xml/schemas</p> <p>Software that is used to generate SQL schemas, RestfulDB metadata and the RestfulDB middleware that allows to publish the databases generated from the XML description on the Web are available at public Subversion repositories:</p> <p> svn://www.crystallography.net/solsa-database-scripts<br> svn://saulius-grazulis.lt/restfuldb</p> <p>Usage<br> -----</p> <p>The unpacked ZIP file will create the "db/" directory with the tree layout given below. In addition to the database description file "main-database-description.xml", all XSD schemas necessary for validation of the XML file are provided. On a GNU/Linux operating system with a GNU Make package installed, the XML file validity can be checked by unpacking the ZIP file, entering the unpacked directory, and running 'make distclean; make'. For example, on a Linux Mint distribution, the following commands should work:</p> <p> unzip main-database-description.zip<br> cd db/release/v0.10.0/tables/<br> sh -x dependencies/Linuxmint-20.1/install.sh<br> make distclean<br> make</p> <p>If necessary, additional packages can be installed using the 'install.sh' script in the 'dependencies/' subdirectory corresponding to your operating system. As of the moment of writing, Debian-10 and Linuxmint-20.1 OSes are supported out of the box; similar OSes might work with the same 'install.sh' scripts. The installation scripts require to run package installation command under system administrator privileges, but they use *only* the standard system package manager, thus they should not put your system at risk. For validation and syntax checking, the 'rxp' and 'xmllint' programs are used.</p> <p>The log files provided in the "outputs/validation" subdirectory contain validation logs obtained on the system where the XML files were last checked and should indicate validity of the provided XML file against the references schemas.</p> <p>Layout of the archived file tree<br> --------------------------------</p> <p> db/<br> └── release<br> └── v0.10.0<br> └── tables<br> ├── Makeconfig-validate-xml<br> ├── Makefile<br> ├── Makelocal-validate-xml<br> ├── dependencies<br> ├── main-database-description.xml<br> ├── outputs<br> └── schema</p>
BCP/Bio-MRSUT 2015. Bio-economic Multi-regional Supply-Use Tables.
<p>BIOCLIMAPATHS is an AXIS-ERANET 2019 granted project, that aims to better understand the impacts of climate change in future societies that have adopted bioeconomy as a substantial pillar of their economies. The project’s main aim – and output – is to provide insights and recommendations for climate resilient and just bioeconomy transition paths for society and economy.</p> <p>The BIOCLIMAPATHS (BCP) consortium leverages on complementary expertise of research teams from Austria, Germany and Spain, developing an innovative, spatially explicit, modelling framework for risk assessments of bioeconomy transitions subject to climate extremes. The project’s main aim – and output – is to provide insights on climate resilient and just bioeconomy transition paths in society.</p> <p>A key tool to achieve this aim is the elaboration of a detailed multisectoral database with high disaggregation on bio-based sectors. For the elaboration of this database, called Bio-MRSUT (Bio-economic Multi-regional Supply-Use Tables) framework, we started from EXIOBASE (Stadler et al. 2018). From the EXIOBASE data to obtaining the series of multi-regional SUT monetary marks, some estimation is required. First, by adapting the initial tables from EXIOBASE to the sectoral structure proposed in BIOCLIMAPATHS. Subsequently, to complete the database with additional information on certain bioeconomy sectors (agriculture, livestock, and biofuels), the 2010 and 2015 BioSAMs (Mainar et al., 2021) carried out by the Joint Research Centre (JRC) of the European Commission have been used, building the pertinent extrapolations to complete the proposed time period. The result of these processes has given rise to multi-regional monetary SUT frameworks for the EU and its Member States with a very broad disaggregation of the bioeconomy sectors. These multiregional frameworks comprise, with reference to the year 2015, a total of 78 activities (44 of Bioeconomy) and 78 goods and services (44 of them bio-economics), for the 28 EU countries (including the United Kingdom) and the Rest of the World, (as well as the interrelationships and bilateral exchanges between all these territories). In addition, they contain the breakdown of final demand and added value, as well as taxes on activities and products and imports by origin (the resulting data matrix contains 4,529 rows and 4,669 columns).</p>
Sentinel-2 derived Sphagnum and herbaceous CI, GCC, NDVI, MSI, SL2P10 LAI, and hourly temperature, water table depth, PAR on the Bernadouze peatland from 2017 to 2021 and 2D scans LAI over 2021.
<p>This release contains data from field campaign over the Bernadouze Peatland and satellite sentinel-2 derived vegetation indices from 2017-01-01 to 2021-12-31.</p> <p>Sentinel-2 derived Sphagnum and herbaceous chlorophyll index, green chromatic coordinate, normalised difference index, moisture soil index retrived on google earth engine from 2017-01-01 to 2021-12-31 on the Bernadouze peatland.</p> <p>Sentinel-2 sphagnum and herbaceous leaf area index (m².m-²) computed with the SL2P10 algorithm from 2017-01-01 to 2021-12-31 thanks to google earth engine.</p> <p>Sphagnum leaf area index (m².m-²), measured with a 2D-scan (LI3100 Area Meter) over the 2021 season on the Bernadouze peatland.</p> <p>Reflectance over the 12 bands of Sentinel-2 on two areas of the Bernadouze peatland : one dominated by Sphagnum mosses and the other by herbaceous vegetation. Data related to an image acquired the 2021-07-21.</p> <p>Hourly air temperature (°C) and photosynthetically active radiations (umol.m-².s-1) derived from the S2M (SAFRAN–SURFEX, ISBA–Crocus–MEPRA) reanalysis chain on the Bernadouze peatland. Vertical resolution of 300m on the 'Couseran' massif.</p> <p>Hourly water table depth (m) from 10 piezometers (PZ1, ..., PZ10) over the Bernadouze peatland. Measured with 10 Orpheus Mini Water Level Logger, OTT HydroMet, Germany.</p> <p>Growth primary productivity of dominant peatland vegetation (umol.m-².s-1) calculated by the difference of measured net primary productivity and of measured ecosystem respiration flux under dark conditions. Measurements of GPP and ER are made with a soil chamber connected to a LI-COR LI-7810 analyser from 2017-01-01 to 2021-12-31 on the Bernadouze peatland.</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.