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11,710 results for “interactions”

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edi48/100

MCR LTER: Coral Reef: Priority effects in coral-macroalgae interactions can drive alternate community paths in the absence of top-down control, data for Adam 2022 Ecology

These data were generated in support of the manuscript: Adam TC, Holbrook SJ, Burkepile DE, Speare KE, Brooks AJ, Ladd MC, Shantz AA, Thurber RLV, and Schmitt RJ, Ecology The outcomes of species interactions can vary greatly in time and space with the outcomes of some interactions determined by priority effects. On coral reefs, benthic algae rapidly colonize the disturbed substrate. In the absence of top-down control from herbivorous fishes, these algae can inhibit the recruitment of reef-building corals, leading to a persistent phase shift to a macroalgae-dominated state. Yet, corals may also inhibit colonization by macroalgae, and thus the effects of herbivores on algal communities may be strongest following disturbances that reduce coral cover. Here, we report results from experiments conducted on the fore reef of Moorea, French Polynesia, where we: 1) tested the ability of macroalgae to invade coral-dominated and coral-depauperate communities under different levels of herbivory, 2) explored the ability of juvenile corals (Pocillopora spp.) to suppress macroalgae, and 3) quantified the direct and indirect effects of fish herbivores and corallivores on juvenile corals. We found that macroalgae proliferated when herbivory was low but only in recently disturbed communities where coral cover was also low. When coral cover was < 10%, macroalgae increased 20-fold within one year under reduced herbivory conditions relative to high herbivory controls. Yet, when coral cover was high (50%), macroalgae were suppressed irrespective of the level of herbivory despite ample space for algal colonization. Once established in communities with low herbivory and low coral cover, macroalgae suppressed recruitment of coral larvae, reducing the capacity for coral replenishment. However, when we experimentally established small juvenile corals (2 cm diameter) following a disturbance, juvenile corals inhibited macroalgae from invading local neighborhoods, even in the absence of herbivore

openCC (other)Jan 2025View details →
OpenNeuro44/100

Multiple interactive memory representations underlie the induction of false memory

Open the record for dataset details and reuse information.

openCC0Jan 2021View details →
zenodo44/100

Dataset - Characterization of Kazachstania humilis and Lactic Acid Bacteria interactions in French sourdoughs

<p>Here you can find the dataset and Rmarkdonw script associated to the scientific paper :&nbsp;Dataset - Characterization of Kazachstania humilis and Lactic Acid Bacteria interactions in French sourdoughs</p>

opencc-by-4.0Feb 2020View details →
zenodo44/100

Project files provided as supporting information to the manuscript "Ligand-protein interactions in lysozyme investigated through a dual-resolution model"

<p><strong>README file for the project files provided as supporting information to the manuscript &quot;Ligand-protein interactions in lysozyme investigated through a dual-resolution model&quot;</strong></p> <p>February 12, 2020</p> <p>Authors: Raffaele Fiorentini, Kurt Kremer and Raffaello Potestio</p> <p>================================</p> <p>Overview</p> <p>The dataset&nbsp;is organised in three (compressed) subfolders (see the tree diagrams in each section):</p> <p>- annihilation<br> - decoupling<br> - density</p> <p>The figure deltaG_binding_ann_dec_comparison.png shows the results of binding free energy calculations comparing the values obtained both for annihilation and decoupling.</p> <p>The figure deltaG_binding_annih_gromacs_espp.png displays the results for Binding FE, comparing the values obtained in GROMACS and ESPResSo++.</p> <p>The README.pdf file contains detailed information about these folders and their content.</p> <p>================================</p> <p>The &quot;annihilation&quot; folder contains all results concerning the calculation of binding free energy in case of annihilation and it is divided in two parts:&nbsp;</p> <p>- complex<br> - ligand</p> <p>In &quot;complex&quot; are reported the results of Ligand-Protein FE both in ESPResSo++ and GROMACS. All simulations are fully-atomistic.&nbsp;</p> <p>In &quot;ligand&quot; are reported the results of ligand solvation free energy both in ESPResSo++ and GROMACS. All simulations are fully-atomistic.&nbsp;</p> <p>====</p> <p>The &quot;decoupling&quot; folder contains all results concerning the calculation of binding free energy in case of decoupling and it is divided in three parts:&nbsp;</p> <p>- complex-DualRes<br> - complex-FullyAT<br> - ligand</p> <p>In &quot;complex-DualRes&quot; are reported the results of Ligand-Protein FE only in ESPResSo++ (GROMACS cannot do decoupling). The system is simulated in Dual-Resolution. It is possible to find the trajectory files in the sub-directories &quot;lambdaindex-0&quot; and &quot;lambdaindex-30&quot;.</p> <p>In &quot;complex-fullyAT&quot; are reported the results of Ligand-Protein FE only in ESPResSo++. The system simulated is fully-atomistic. It is possible to find the trajectory file in the sub-directories &quot;lambdaindex-0&quot; and &quot;lambdaindex-30&quot;.</p> <p>In &quot;ligand&quot; are reported the results of ligand solvation free energy only in ESPResSo++. All simulations are fully-atomistic. It is possible to find the trajectory file in the sub-directories &quot;lambdaindex-0&quot; and &quot;lambdaindex-20&quot;.</p> <p>====</p> <p>The &quot;density&quot; folder contains the data for the tuning of the c parameter of the steric repulsion among residues. This parameter is tuned so that the water density attains the value computed in all-atom simulations.</p>

opencc-by-4.0Feb 2020View details →
zenodo44/100

Collection of global datasets for the study of floods, droughts and their interactions with human societies

<p>This is a collection of 134 global and free datasets allowing for spatial (and temporal) analyses of floods, droughts and their interactions with human societies.&nbsp;We have structured the datasets into seven categories: hydrographic baseline, hydrological dynamics, hydrological extremes, land cover &amp; agriculture, human presence, water management, and vulnerability. Please refer to <a href="https://doi.org/10.1002/wat2.1424">Lindersson et al. (2020)</a>&nbsp;for further information about review methodology.</p> <p>The collection is a descriptive list, holding the following&nbsp;information for each dataset:&nbsp;</p> <ul> <li>Category<em> - as structured in Lindersson et al. (2020).</em></li> <li>Sub-category<em>- as structured in Lindersson et al. (2020).</em></li> <li>Abbreviation -&nbsp; <em>official or as specified in Lindersson et al. (2020).</em></li> <li>Title <em>- full title of dataset.</em></li> <li>Product(s)<em>&nbsp;- type of product(s) offered by the dataset.</em></li> <li>Period<em> - time period covered by the dataset, not defined for all datasets.</em></li> <li>Temporal resolution<em> - not defined for static datasets.</em></li> <li>Angular spatial resolution<em> - only defined for gridded datasets.</em></li> <li>Metric spatial resolution <em>- only defined for gridded datasets.</em></li> <li>Map scale</li> <li>Extent<em> - geographic coverage of dataset given in latitude limits.</em></li> <li>Description</li> <li>Creating institute(s)</li> <li>Data type<em>&nbsp;- raster, vector or tabular.</em></li> <li>File format</li> <li>Primary EO type<em>&nbsp;- specifies if the product primarily is based on remote sensing, ground-based data, or a hybrid between remote sensing and ground-based data.</em></li> <li>Data sources<em>&nbsp;- lists the data sources behind the dataset, to the extent this is feasible.</em></li> <li>Data sources also in this table<em>&nbsp;- data sources that are also included as datasets in this collection.</em></li> <li>Intentionally compatible with<em>&nbsp;- defines other datasets in this collection that the dataset is intentinoally compatible with.</em></li> <li>Citation<em>&nbsp;- dataset reference or credit.</em></li> <li>Documentation&nbsp;<em>- dataset documentation.</em></li> <li>Web address<em>&nbsp;- dataset access link.</em></li> </ul> <p>NOTE:&nbsp;Carefully consult the data usage licenses as given by the data providers, to assure that the exact permissions and restrictions are followed.</p>

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

Analogue models testing the interaction between a propagating continental rift and inherited crustal fabrics

<p>This dataset presents the results of an experimental series of analogue models performed to investigate the interaction between a propagating continental rift and inherited crustal fabrics. Our experimental series was designed adopting a parametric approach, which consisted in the systematic variation of the orientation of various kinds of brittle discontinuities (e.g., faults, fractures, foliations, etc.). Structures of models have been analysed quantitatively by means of photogrammetric digital elevation model reconstruction and semi-automatic fault pattern quantification. In this dataset, we show the row data and specific elaborations supporting the interpretation of results.</p>

opencc-by-4.0Mar 2020View details →
zenodo44/100

The Unfolding Journey of Superoxide Dismutase 1 Barrels Under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions With Crowders

<p>This data&nbsp;accompanies the&nbsp;article entitled <em>The Unfolding Journey of Superoxide Dismutase 1 Barrels Under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions With Crowders</em>, published in J. Phys. Chem. Lett.&nbsp;(<a href="https://doi.org/10.1021/acs.jpclett.0c00699">https://doi.org/10.1021/acs.jpclett.0c00699</a>).</p> <p><strong>01_SOD1bar_unfolding_REST2.zip:&nbsp;</strong>The zip archive&nbsp;includes REST2&nbsp;trajectories for the three systems investigated in the paper: 1:1 packing, 2:1 packing, and the dilute case. The trajectories are saved in the GROMACS XTC file format, separately for each temperature (i=0,...,23). Given the large trajectory sizes, only protein coordinates (SOD1bar + crowders) are reported, and the output frequency is reduced to&nbsp;100 ps.&nbsp;A starting geometry (in the Gromos87 GRO format)&nbsp;after equilibration of the initial packing&nbsp;is provided for each REST2 simulation (conf_prot.gro).&nbsp;Moreover, for each REST2 simulation, an xarray (http://xarray.pydata.org) dataset, saved in the netCDF file format,&nbsp;is included with computed fraction&nbsp;of native contacts,&nbsp;secondary structure content, and the Calpha RMSD of the barrel core (beta sheets beta1 - beta8)&nbsp;with respect to the crystal structure.</p> <p><strong>02_SOD1bar_geometries_representative_unfolding.zip:</strong>&nbsp;Representative&nbsp;SOD1bar geometries along the unfolding pathway (presented in Figure 3 of the paper).</p> <p><strong>03_SOD1bar_geometries_loopVII.zip:&nbsp;</strong>SOD1bar&nbsp;geometries with varying loop VII conformation which were&nbsp;isolated from dilute REST2 and which are presented in Figure&nbsp;S9 of the paper.</p>

opencc-by-4.0May 2020View details →
zenodo44/100

Dataset associated with article "Robots mediating interactions between animals for interspecies collective behaviors"

<p>This dataset contains results and analysis described in the study &quot;Robots mediating interactions between animals for interspecies collective behaviors&quot;,&nbsp;Bonnet, F., Mills, R., Szopek, M., Sch&ouml;nwetter-Fuchs, S., Halloy, J., Bogdan, S., Correia, L., Mondada, F. and&nbsp;Schmickl, T. (2019),&nbsp;<em>Science Robotics</em>,&nbsp;<em>4</em>(28), doi:&nbsp;10.1126/scirobotics.aau7897</p> <p>Contents:&nbsp;</p> <ul> <li>experimental&nbsp;data (logs from robotic systems, example videos)</li> <li>animal tracking analysis output</li> </ul> <p>See the readme and summary files contained within the archives for further details.</p>

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

Scored protein-protein interactions accompanying "A pan-plant protein complex map reveals deep conservation and novel assemblies"

<p><a href="http://plants.proteincomplexes.org/static/data/panplant_cfms_scores_annot.txt.gz">All scored pairwise protein-protein interactions with CF-MS scores (3,076,999 unique pairwise interactions)</a></p> <ul> <li>Description: Scores between Orthogroups with the corresponding CF-MS score and eggNOG generated orthogroup descriptions.</li> <li>Note: Only the highest scoring pairs are considered significant. A CF-MS score &gt;= 0.509 corresponds to 10% FDR, &gt;= 0.207 corresponds to 50% FDR</li> <li>Format: OrthogroupID1 [tab] OrthogroupID2 [tab] Score [tab] Annotation1 [tab] Annotation2</li> </ul>

opencc-by-4.0Feb 2020View details →
zenodo44/100

An interactive figure of the 2016 and 2020 X-ray light curves of LMC 1968 as observed by the XRT instrument on Swift

<p>This repository contains all the files necessary to create the interactive figure in the Research Note ov Schwarz, Page, Kuin, &amp; Darnley 2020. The figure was created using the <a href="https://aas-timeseries.readthedocs.io/en/latest/">aas-timeseries</a> package of the <a href="https://www.astropy.org">astropy</a> project. The file lmc68.py is the underlying python code while the two lmcrel*.csv are the input files for the 2016 and 2020 eruptions of the recurrent nova LMC 1968 as observed by the XRT instrument on board the Neil Gehrels Swift observatory. A Jupyter notebook is required to preview the interactive figure. The output from the code is saved in the interactive.tar.gz package. It consists of four files:</p> <ul> <li>index.html</li> <li>figure.json</li> <li>data_75e74aca-09f1-4846-966e-9e33c7acc8d3.csv</li> <li>data_5402e718-01cf-4ad7-92a5-7679d4076ed5.csv</li> </ul> <p>The first file, index.html, is the html framework that houses the interactive figure. figure.json contains&nbsp;the interactive figure commands while the two data*csv files are the underlying data.&nbsp;The interactive figure can be viewed if this package is opened on a web server. &nbsp;A copy of this interactive figure is available <a href="https://authortools.aas.org/LMC1968/">here</a>&nbsp;so you can try it out.</p>

opencc-by-4.0Aug 2020View details →
Figshare44/100

Spike-ACE2 interaction overview

<p>UnityMol 3D model export related to FAIR sharing of molecular visualization experiences illustrated with COVID-19-related data. See our paper (to come)</p>

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

Human Pleckstrin Homology domain Interacting Protein (PHIP); A Target Enabling Package

<p>SGC Oxford has expressed, purified and crystallized the second bromodomain of PHIP as part of the probe programme. Fragment screening and X-ray crystallography identified binders, some of which optimised to uM affinity. However, molecules with probe properties were not obtained. Consequently it has been decided to put the information generated into the public domain.</p>

opencc-by-4.0Jun 2016View details →
zenodo44/100

Transcriptome analysis of the effect of over-expressing H2A.J mutants in proliferating WI38 fibroblasts for the paper entitled: The H2A.J histone variant contributes to Interferon-Stimulated Gene expression in senescence by its weak interaction with H1 and the derepression of repeated DNA sequences

<p>Abstract for overall study:</p> <p>The histone variant H2A.J was previously shown to accumulate in senescent human fibroblasts with persistent DNA damage to promote inflammatory gene expression, but its mechanism of action was unknown. We show that H2A.J accumulation contributes to weakening the association of histone H1 to chromatin and increasing its turnover. Decreased H1 in senescence is correlated with increased expression of some repeated DNA sequences, increased expression of STAT/IRF transcription factors, and transcriptional activation of Interferon-Stimulated Genes (ISGs). The H2A.J-specific Val-11 moderates the transcriptional activity of H2A.J, and H2A.J-specific Ser-123 can be phosphorylated in response to DNA damage with potentiation of its transcriptional activity by the phospho-mimetic S123E mutation. Our work demonstrates the functional importance of H2A.J-specific residues and potential mechanisms for its function in promoting inflammatory gene expression in senescence.</p> <p>Specific description for this dataset:</p> <p>H2A.J differs from canonical H2A only by a valine at position 11 instead of alanine, and the 7 C-terminal amino acids containing a potential minimal phosphorylation site SQ for DNA-damage response kinases. To test the functional importance of these H2A.J-specific sequences, we mutated Val-11 to Ala as is found in all canonical H2A sequences, and we mutated Ser-123 to either Glu to mimic a phospho-serine residue or to Ala to prevent phosphorylation. We also substituted the C-terminus of H2A.J with the C-terminus of H2A. These mutants, WT-H2A.J and canonical H2A-type1 were ectopically expressed in proliferating fibroblasts, and their microarray transcriptomes were compared to that of proliferating and senescent fibroblasts without ectopic histone expression. Genome-wide transcriptome analysis indicated that senescent fibroblasts clustered distinctly from proliferating fibroblasts, and proliferating fibroblasts expressing the H2A.J-V11A and H2A.J-S123E mutants clustered distinctly from fibroblasts expressing the other H2A.J mutants, WT-H2A.J, and H2A. Hallmark gene set enrichment analysis of the transcriptomes of fibroblasts expressing H2A.J-V11A or H2A.J-S123E versus control proliferating fibroblasts indicated that they showed the same highly significant enrichment for the Epithelial-Mesenchyme Transition, TNF-Alpha Signaling Via NF-kB, and Inflammatory Response gene sets. Notable inflammatory genes including IL1A, IL1B, IL6, CXCL8, and CCL2 are contained in these gene sets and are often induced in senescence as part of the senescence-associated secretory phenotype. Heat maps showed that the H2A.J-V11A and H2A.J-S123E mutants were particularly apt at activating the expression of these inflammatory genes in proliferating fibroblasts</p>

opencc-by-4.0Nov 2020View details →
zenodo44/100

Dataset for "Partitioned fault movement and aftershock triggering: evidence for fault interactions during the 2017 Mw 5.4 Pohang earthquake, South Korea"

<p>This repository contains the seismograms of the Korea Institute of Geoscience and Mineral Resources (KIGAM) and the Korea Institute of Nuclear Safety (KINS)&nbsp;used in Son et al. (2020). The uploaded waveforms were filtered according to the Supporting Information of Son et al. (2020).&nbsp;Continuous waveforms are available via&nbsp;the Korea Meteorological Administration&nbsp;(KMA; http://necis.kma.go.kr).</p> <p>Suggested citation: Son, M., Cho, C. S., Lee, H. K., Han, M., Shin, J. S., Kim, K., Kim, S. (2020). Partitioned fault movement and aftershock triggering: evidence for fault interactions during the 2017 Mw 5.4 Pohang earthquake, South Korea. Journal of Geophysical Research: Solid Earth,&nbsp;e2020JB020005.&nbsp;<a href="https://doi.org/10.1029/2020JB020005">https://doi.org/10.1029/2020JB020005</a></p>

opencc-by-4.0Nov 2020View details →
zenodo44/100

Mining API Interactions to Analyze SoftwareRevisions for the Evolution of Energy Consumption (MSR'2021 Dataset)

<p><strong>Motivation</strong></p> <p>This repository contains the data-set used as a basis for our MSR&#39;2021 paper&nbsp;<em>Mining API Interactions to Analyze Software Revisions for the Evolution of Energy Consumption</em>.</p> <p><strong>Description of the dataset</strong></p> <p>The dataset is stored in a file <em>msr_2021_dataset.csv</em>&nbsp;and contains the following data:</p> <ul> <li>id&nbsp;- an individual identifier</li> <li>sampleNr - a number identifying the group this sample relates to</li> <li>name&nbsp;- the name of the library examined</li> <li>className&nbsp;- the class name as an abbreviation</li> <li>method&nbsp;- the name of the executed method</li> <li>duration&nbsp;- duration of method execution</li> <li>durationAdjusted - duration after alignment between method trace and energy profile</li> <li>energyConsumption&nbsp;- computed energy consumption</li> <li>watts&nbsp;- recorded wattage</li> <li>`package-names` - per package uAPI profile</li> <li>uApi&nbsp;- the computed uAPI profile value</li> </ul> <p>The files <em>joule_anova_posthoc_result.csv</em> and <em>uAPI_anova_posthoc_result.csv</em> contain the results of the ANOVA and Tukey HSD posthoc analysis to determine accuracy and F1-score of the presented approach.</p> <p>&nbsp;</p> <p><strong>License</strong></p> <p>Creative Commons CC-BY</p>

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

Agonum sordidum, Fig_6 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.

<p>New version as *png</p> <p>Agonum sordidum,</p> <p>Fig_6 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>

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

Agonum rugicolle, Fig_5 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.

<p>New version as *png</p> <p>Agonum rugicolle,</p> <p>Fig_5 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>

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

Agonum_nigrum, Fig_4 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.

<p>New version as *png</p> <p>Agonum_nigrum,</p> <p>Fig_4 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>

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

Agonum_mesostictum, Fig_2 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.

<p>New version as *png</p> <p>Agonum_mesostictum,</p> <p>Fig_2 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>

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

Agonum monachum syriacum, Fig_3 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.

<p>New version as *png</p> <p>Agonum monachum syriacum,</p> <p>Fig_3 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>

opencc-by-4.0Jun 2021View details →

ScienceDex guides

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

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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