Skip to main content
Powered by ShareScore

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.

15,128

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

15,128 results for “Outcome”

Learn how ShareScore rates datasets ↗
zenodo48/100

A Curated Gene and Biological System Annotation of Adverse Outcome Pathways Related to Human Health

<p>Adverse Outcome Pathways (AOPs) are multi-scale models of biological mechanisms connecting molecular initiating events to adverse outcomes through measurable key events.&nbsp;AOPs can guide the use and development of new approach methodologies (NAMs) aimed at reducing animal experimentation in chemical safety assessment. Here, we present a comprehensive molecular annotation of AOPs relevant to human health to embed the AOP framework into molecular data interpretation, which supports the development and application of novel AOP-based approaches in biomedical research.</p> <p>Please cite the following publication alongside this Zenodo entry when using the data:</p> <p>Saarim&auml;ki, L.A., Fratello, M., Pavel, A.&nbsp;<em>et al.</em>&nbsp;A curated gene and biological system annotation of adverse outcome pathways related to human health.&nbsp;<em>Sci Data</em>&nbsp;<strong>10</strong>, 409 (2023). https://doi.org/10.1038/s41597-023-02321-w</p>

opencc-by-4.0Oct 2022View details →
zenodo44/100

ACF database on the vitamin A and iron outcomes from the MANGO trial

<p>This dataset contains the variables used in the analysis of the vitamin A and iron&nbsp;outcomes of the MANGO trial&nbsp;carried out in Burkina Faso between 2016 and 2018.&nbsp;</p>

opencc-by-4.0Dec 2019View details →
zenodo44/100

Data from: "Correlates of mid-winter pregnancy and early reproductive outcomes in a reintroduced elk (Cervus canadensis) population"

<p>Raw and processed datasets used for analysis in "Correlates of mid-winter pregnancy and early reproductive outcomes in a reintroduced elk (<em>Cervus canadensis</em>) population" by Hooven et al., published in <em>Mammalian Biology</em>. Datasets are as follows:</p> <p>Pregnancy.csv - Raw dataset detailing year and date of capture, individual identifier, and measured intrinsic variables, along with confirmed or predicted pregnancy/calf viability status.</p> <p>Pregnancy_final_mass.csv - Raw dataset after body mass estimation for individuals that were not weighed.&nbsp;</p> <p>all_confirmed_preg.csv - Subset of raw data for all individuals with confirmed pregnancy status (via lab PSPB assay).</p> <p>preg_ageclass.csv - Subset of all_confirmed_preg dataset including all individuals with general age classification (e.g., adult or subadult).</p> <p>preg_numeric.csv - Subset of all_confirmed_preg dataset including all individuals with numeric age value (from incisiform canine cementum annuli).</p> <p>all_fns.csv - Subset of dataset including all individuals with confirmed or predicted fetal/early neonatal survival ("offspring viability") status.</p> <p>fns_ageclass.csv - Subset of all_fns.csv including all individuals with general age classification.</p> <p>fns_numeric.csv - Subset of all_fns.csv including all individuals with numeric age values.</p> <p>parameter_est.csv - Parameter estimates from top-performing generalized linear mixed models for both pregnancy and offpsinrg viability, for plotting.</p>

opencc-by-4.0Mar 2024View details →
zenodo44/100

Flood Hazard Maps and Associated Data for Case Study: Funding rules that promote equity in climate adaptation outcomes

<p>Inundation grids for multiple return periods and multiple scenarios. Please see the underlying study for more details about the methods. The data here can be reproduced following the code and instructions at this repository: https://github.com/CoRE-Lab-UCF/Pollack_et_al_2024/tree/main. Also available here: https://doi.org/10.5281/zenodo.14515896.&nbsp;</p>

opencc-by-4.0Dec 2024View details →
zenodo44/100

Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing

<p><strong>Open data repository,&nbsp;Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing</strong></p> <p><strong>Latest version of files: repository_v2.0.zip, Behavior Data_v2.0.xlsx and MRI IDs Testing&amp;Replication Cohort.xlsx (please ignore repository.zip)</strong></p> <p>Open data repository Knab et al. Prediction of stroke outcome in mice based on non-invasvive MRI and behavioral testing</p> <p>Open code and documentation of prediction models available via&nbsp;<a href="https://github.com/major-s/mouse-mcao-outcome-predictor">https://github.com/major-s/mouse-mcao-outcome-predictor</a></p> <p><strong>Content:</strong></p> <p>README.txt</p> <p>This information</p> <p><strong>dat</strong></p> <p>Contains MRI data in NIFTI format and secondary data from atlas registration. For documentation of atlas registration files see https://pubmed.ncbi.nlm.nih.gov/28829217/<br>Files used for the manuscript:<br>t2.nii: t2 weighted image acquired 24 h post stroke<br>masklesion.nii: manually delineated lesion<br>x_masklesion.nii: lesion in atlas space<br>ix_ANO.nii: Allen brain atlas in native space (i.e. matching t2.nii)<br>Lesion volume was calculated by volume of voxels unequal 0 in x_masklesion.nii<br>Overlap of regions defined by ix_ANO.nii with masklesion.nii were used for calculating percent damage in each atlas region</p> <p><strong>prediction_models</strong></p> <p>Contains separated training and test data as xlsx and csv files with lesion volumes in cubic mm of the Allen brain atlas space, percent damage per atlas region and behavioral data. The training data was used as input for training prediction models in MATLAB, the results were created using the test data.<br>The files have following sturcture:<br>Column 1: animal ID<br>Columns 2-537: MRI regions (column title corresponds to the region number as used in the Allen common coordinate framework)<br>Column 538: lesion volume<br>Column 539: initial performance (subacute deficit) = mean performance/deficit on days 2-6<br>Column 540: mean performance/deficit on days 2-6 = initial performance (subacute deficit) - this column equals column 539 but has different header which was used to train the residual from initial deficit<br>Column 541: residual performance/deficit<br>Column 542: test or training group<br>Consecutive rows contain data for each animal specified by the animal id</p> <p>The repository also contains all trained models, prediction results for the test data and tables with resulting median absolute error (MedAE) and 5th, 25th, 75th and 95 absolute error quantiles for each model.<br>The model files end with '_models.mat' and contain 50 independently trained models each. Each model version is specified by number 1-50.<br>The result files end with '_test_results.mat' or '_test_results.xlsx', files with MedAE and quantiles end with '_test_errors.xlsx' or '_test_errors.csv. The common part of filenames specifies the used paradigm<br>Folder 'subacute deficit prediction' contains:<br>&nbsp;- initial_performance_from_lesion_volume: prediction of subacute deficit using lesion volume<br>&nbsp;- initial_performance_from_segmented_mri: prediction of subacute deficit using segmented mri<br>Folder 'long-term outcome prediction' contains:<br>&nbsp;- lesion_volume: prediction of residual deficit using lesion volume<br>&nbsp;- segmented_mri: prediction of residual deficit using segmented_mri<br>&nbsp;- initial_performance: prediction of residual deficit using subacute deficit<br>Folder 'mri_inc_oob_imp' contains models trained using increasing number of mri segments sorted according to the out-of-bag importance. &nbsp;The number of used segments is given in the file name. The models, results and errors are separated in subfolders.</p> <p>Files with equal file name and different extension always contain the same data</p> <p><strong>templates</strong><br>Allen atlas, template, brain mask, hemisphere masks, tissue probability masks in NIFTI format including annotations of region IDs and parameter.m file for use in MATLAB toolbox ANTx2<br>&nbsp;</p>

opencc-by-4.0May 2022View details →
zenodo44/100

Long term effects of payment for performance on maternal and child health outcomes– evidence from Tanzania

<p>These are the datasets underpinning the paper entitled:&nbsp;<strong>Long term effects of payment for performance on maternal and child health outcomes&ndash; evidence from Tanzania.</strong></p> <p><strong>The datasets are provided in csv and Stata 16 format along with variable descriptions, and the Stata do file used for analysis.</strong></p>

opencc-by-4.0Oct 2021View details →
zenodo44/100

Stimulation of medial amygdala GABA neurons with kinetically different channelrhodopsins yields opposite behavioral outcomes

<p>This dataset continues the dataset accessible by doi 10.5281/zenodo.4311847. The latter also contains all the relevant metadata description.</p>

opencc-by-4.0Dec 2021View details →
zenodo44/100

Data for: Polystyrene nanoplastics differentially influence the outcome of infection by two microparasites of the host Daphnia magna

<p>This dataset supports the findings of the study 'Polystyrene nanoplastics differentially influence the outcome of infection by two microparasites of the host <em>Daphnia magna</em>', published in Philosophical Transactions of the Royal Society B (https://doi.org/10.1098/rstb.2022.0013).</p>

opencc-by-4.0Jun 2022View details →
zenodo44/100

Data and Code for "Early complications after mild to moderate ischemic stroke and their impact on 3-months outcome: The prospective Stroke Unit Plus Cohort Study"

<p>This repository consists of the data and code for the publication &quot;Early complications after mild to moderate ischemic stroke and their impact on 3-months outcome: The prospective Stroke Unit Plus Cohort Study&quot;<br> <br> - Analysis code:<br> &nbsp; &nbsp;- Analysis.R<br> &nbsp; &nbsp;- Functions.R</p> <p>- Data:<br> &nbsp; &nbsp;- AnalysisSet in .Rdata, .csv, and .xlsx formats<br> <br> - Variable codebook in .xlsx format</p> <p>Responsibility for the upload lies with Prof. Jan Sobesky, e-mail:&nbsp;j.sobesky@ak-neuss.de<br> For inquiries regarding the data please contact Dr. Vince Madai, e-mail: vince_istvan.madai@bih-charite.de</p>

opencc-by-4.0Aug 2022View details →
zenodo44/100

LMMA perceptions of outcomes data

<p>Data collected in Madagascar in May and&nbsp;June 2017 forming part of a PhD thesis and paper on the perceptions of adopters of Locally Managed Marine Areas (LMMAs).&nbsp;</p>

opencc-by-4.0Dec 2021View details →
zenodo44/100

Data from: Tracking the popularity and outcomes of all bioRxiv preprints

<p>The data used to generate figures in the manuscript titled <a href="https://www.biorxiv.org/content/early/2019/01/13/515643">&quot;Tracking the popularity and outcome of all bioRxiv preprints,&quot;</a> posted to bioRxiv 13 Jan 2019.</p> <ul> <li><strong>22 Mar 2019:</strong> PDFs of each figure from the paper have been added to the repository. In addition, the license has been changed from CC-BY-NC to CC0.</li> </ul>

opencc-zeroJan 2019View details →
zenodo44/100

MiRoR11 - P2 - Annotated corpus for primary and reported outcomes extraction

<p>Annotated corpus for outcome extraction</p> <p>This folder contains 2 subfolders:<br> 1. Primary_outcomes - a corpus annotated for primary outcomes<br> The folder contains the following files:<br> po_sent_marked_p1_1000.txt - sentences 1 - 1000 of the annotated corpus, ConstruKT format; coordinated outcomes annotated as single entity<br> po_sent_marked_p2_1000.txt - sentences 1001 - 2000 of the annotated corpus, ConstruKT format; coordinated outcomes annotated as single entity</p> <p>po_sent_marked_col_p1.txt - sentences 1 - 1000 of the annotated corpus, tabulated format; coordinated outcomes annotated as single entity<br> po_sent_marked_col_p2.txt - sentences 1001 - 2000 of the annotated corpus, tabulated format; coordinated outcomes annotated as single entity</p> <p>po_sent_marked_col_p1_coord.txt - sentences 1 - 1000 of the annotated corpus, tabulated format; coordinated outcomes annotated as separate entities<br> po_sent_marked_col_p2_coord.txt - sentences 1001 - 2000 of the annotated corpus, tabulated format; coordinated outcomes annotated as separate entities</p> <p>Subfolders:<br> po - the corpus for 10-fold cross-validation (10 subfolders with train/dev/test sets); coordinated outcomes annotated as separate entities<br> po_coord - the corpus for 10-fold cross-validation (10 subfolders with train/dev/test sets); coordinated outcomes annotated as separate entities</p> <p>2. Reported_outcomes - a corpus annotated for reported outcomes<br> The corpus contains sentences from Results and Conclusions sections of the articles for which primary outcomes were annotated. The first part of reported outcomes corpus contains sentences from articles for the first half of the primary outcomes corpus (sentences 1 - 1000). The second part of reported outcomes corpus contains sentences from articles for the second half of the primary outcomes corpus (sentences 1001 - 2000).</p> <p>The folder contains the following files:<br> res_sent_marked_p1.txt - first part of the annotated corpus, ConstruKT format<br> res_sent_marked_p2.txt - second part of the annotated corpus, ConstruKT format</p> <p>res_sent_marked_p1_col.txt - first part of the annotated corpus, tabulated format<br> res_sent_marked_p2_col.txt - first part of the annotated corpus, tabulated format</p> <p>Subfolders:<br> rep - the corpus for 10-fold cross-validation (10 subfolders with train/dev/test sets)</p>

opencc-by-4.0May 2019View details →
zenodo44/100

Data, Analytical Code, and Model Outputs From: "Green is the New Black: Outcomes of Post-Fire Tree Planting Across the Interior West, USA"

<p>This archive includes data (locations of tree plantings, one-year survival records, remotely sensed canopy cover change), statistical code, and model outputs from Rodman et al. (2024). For more information on specific information, processing methods, and data formats, see "README.md" or "README.html" files associated with this archive</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Characterization of Metabolism Associated with Outcomes in Severe Acute Pancreatitis: Insights from Serum Metabolomic Analysis

<p>1H NMR spectra data of SAP patients (Survivors/ Non-survivors). The spectra were binned as 0.02 ppm spectral buckets. The chemical shift regions corresponding to the water region and TSP were excluded to avoid spectral interference. This dataset was used for the metabolomics related study to highlight the dysregulation of metabolites in the study group.</p> <p>&nbsp;</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

DATASETS and OUTCOMES - Assessment of intrinsic aquifer vulnerability at continental scale through a critical application of the DRASTIC method: the case of South America

<p>A robust and comprehensive assessment of intrinsic aquifer vulnerability at continental scale map may represent an essential initial step towards a more sustainable land-use and water management.</p> <p>This repository contains the outcomes of an intrinsic aquifer vulnerability assessment of South America, performed by the DRASTIC method. The assets included in this repository are mainly raster maps (.tif, .geotif), created and georeferenced in QGIS (v3.16). Coordinate reference system (CRS) of the dataset is WGS84.</p> <p>Technical specifications of all graphical outcomes are stored in a dedicated file (README.txt).</p>

opencc-by-4.0Oct 2021View details →
zenodo44/100

Adverse Outcome Pathway Wiki RDF

<p>This dataset is the RDF generated from the AOP-Wiki data release (<a href="https://aopwiki.org/downloads">aopwiki.org/downloads</a>). It was generated using a Jupyter notebook that is available on GitHub (<a href="https://github.com/marvinm2/AOPWikiRDF">github.com/marvinm2/AOPWikiRDF</a>), and the process and additional description of the RDF have been published (<a href="https://doi.org/10.1089/aivt.2021.0010">doi.org/10.1089/aivt.2021.0010</a>).</p>

opencc-by-4.0Aug 2024View details →
zenodo44/100

Data from Time since liver transplantation and immunosuppression withdrawal outcomes: a systematic review with individual patient data meta-analysis

<p>This record provides one CSV file containing anonymized individual patient data (IPD) of pre-withdrawal times (in days) of liver transplant recipients that underwent immunosuppression (IS) withdrawal. Collection and publication of anonymized data was approved by the Ethics Committee Northwest and Central Switzerland. Patients of 15 primary studies are stratified by successfully reaching the state of IS-free operational tolerance (OT) or by developing signs of immunological rejection (non-OT).</p>

opencc-by-4.0Dec 2022View details →
zenodo44/100

Data on public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland

<p>A public participatory GIS -survey dataset detailing public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland.</p>

opencc-by-4.0Feb 2023View details →
zenodo44/100

Repository of Raw Datasets for the Study of Anticoagulation and the Incidence of Stroke and Other Outcomes in Patients with Left Ventricular Thrombus

<p>The optimal duration of anticoagulation in patients with left ventricular thrombus (LVT) is unknown. The data package herein presented contains the data used to assess the effect of duration of anticoagulation in the incidence of stroke in patients with left ventricular thrombus (LVT) in a tertiary hospital. These data includes clinical and demographic information, &nbsp;treatment choices (vitamin K antagonists [VKA] versus direct oral anticoagulants [DOAC]), duration of treatment, reason for interruption of treatment, occurrence of stroke, acute myocardial infarction, bleeding events, thrombus resolution and recurrence, and death.<br> The raw dataset is available upon request to the corresponding author.</p>

opencc-by-4.0Dec 2022View details →
zenodo44/100

Datasets used for the manuscript: "Sibling competition, dispersal and fitness outcomes in humans"

<p>Datasets used for the manuscript: &ldquo;Sibling competition, dispersal and fitness outcomes in humans&rdquo;, 10.1038/s41598-023-33700-3</p>

opencc-by-4.0Apr 2023View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record