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11,869 results for “metabolic”
Whole-lake metabolism in arctic-alpine lakes
<p>This dataset contains daily and seasonal averages of whole-lake metabolism in 43 arctic-alpine Swedish lakes, as well as meteorological and lake physical conditions. Metabolism was estimated based on the free-water dissolved oxygen (DO) method following the maximum likelihood estimation approach by Solomon et al. (2013, <em>Limnology & Oceanography</em>) and using scripts by Windslow et al. 2016 (<em>Inland Waters</em>; R package LakeMetabolizer). The dataset is described in a manuscript submitted to <em>Limnology and Oceanography</em>.</p> <p>Changes in version 1.01 relative to original version: We corrected negligible mistakes in the metabolism data (third decimal of seasonal mean gross primary production, ecosystem respiration and net ecosystem production).</p>
MERRIN: MEtabolic Regulation Rule INference from time series data (Docker image and notebooks)
<p>This record contains notebooks and Docker image for reproducing the results of the paper "MERRIN: MEtabolic Regulation Rule INference from time series data" published as part of the ECCB 2022 conference.</p> <p>Notebooks can be executed interactively within the Docker image <code>bioasp/merrin:v1</code> which extends the <a href="http://colomoto.org/notebook">CoLoMoTo Docker</a> version <code>2021-02-01.</code></p> <p>Also see <a href="https://github.com/bioasp/merrin-covert">https://github.com/bioasp/merrin-covert</a></p> <p>The Docker image can be executed as follows:</p> <pre><code class="language-bash">docker pull bioasp/merrin:v1 docker run -it --rm -p 8888:8888 bioasp/merrin:v1 </code></pre> <p>then point your browser to <a href="http://127.0.0.1:8888">http://127.0.0.1:8888</a>.</p> <p>The image can be imported using the command <code>docker load</code> with the image file provided in this record:</p> <pre><code>docker load -i image.tar.gz</code></pre> <p>or with the <code>donodo</code> command available at <a href="https://github.com/pauleve/donodo">https://github.com/pauleve/donodo</a>:</p> <pre><code>pip install -U donodo donodo pull 10.5281/zenodo.6670165</code></pre>
A neuro-metabolic account of why daylong cognitive work alters the control of economic decisions
<p>This is the data to reproduce the main analysis of the article "A neuro-metabolic account of why daylong cognitive work alters the control of economic decisions".</p> <p>Please contact antonius.wiehler@gmail.com if you have any questions.</p>
Metabolic scaling, growth, and reproduction data for animals
<p>Data for the scaling of metabolic rate, rates of growth, and annual reproduction for animals. Data and R scripts associated with "Metabolic scaling is the product of life history optimization"</p>
URBANWASTE - Dataset 1 URBAN_METABOLISM_DATA
<p><strong>General description</strong></p> <p>Within URBANWASTE Work Package 2 data from the pilot cases needed to perform the metabolic analysis was collected. In this sense, mainly data regarding <strong>waste generation and management, tourism (accommodation capacity, tourist flows, tourism economy) and socio-economic data</strong> of each pilot was collected.</p> <p>The indicator sets finally collected were previously cross-checked with the 11 URBANWASTE Pilot Cases regarding data availability on pilot case scale to ensure their suitability and practicability to answer specific URBANWASTE questions. This cross-checking was done by the means of performing a “Survey on data availability” within Task 2.3.</p> <p><strong>Origin, Nature and scale of data</strong></p> <p>For data collection, all pilot cases partners received an empty excel database divided into three thematic areas (waste related data, socio-economic data and tourism related data). In case the pilot case partners did not have access to the requested information, other organisations such as local municipal departments, waste management companies, tourism associations, national statistical agencies etc. were contacted by them for support in data provision.</p> <p>The data collected with these databases mainly represent statistical data. For transparency reasons, data sources were to be specified as well.</p> <p>The spatial scale of the collected data was supposed to be the pilot case area (meaning for the whole city, municipality or metropolitan area). As data on this small scale was not available for all data sets, some of the provided data is on regional or even national level. For ensuring transparency, the spatial scale had to be specified for each data set. According to the type of indicators, the temporal scale varies from annual data to monthly data.</p> <p>For selected data sets, time series data at annual scale were collected for the period 2000 – 2015. For some selected data sets (e.g. waste quantities, tourist arrivals & overnight stays), additionally, also time series on monthly scale were collected for the period 2013 – 2015.</p> <p><strong>Data Format</strong></p> <p>The database prepared to collect the data needed for performing the metabolic analysis was divided into three thematic areas, which are further divided in categories as indicated below:</p> <p><em><strong>Waste related data</strong></em></p> <p>- Waste generation and waste quantities [number]</p> <p>- Waste prevention [text] [number]</p> <p>- Waste management [number] [%] [€]</p> <p><em><strong>Socio-economic data</strong></em></p> <p>- Description of the pilot case [number] [km²]</p> <p>- Economy [number] [%] [€]</p> <p>- Society [number] [%]</p> <p>- Building statistics [%]</p> <p><em><strong>Tourism related data</strong></em></p> <p>- Tourism economy [€]</p> <p>- Accommodation capacity [number]</p> <p>- Tourist flows [number]</p> <p>- Other tourism related information<strong> </strong>[number]</p> <p>Each category contains a lot of indicators, each indicator being identified by a data ID, a unit, and a spatial scale. Data sources had to be specified as well. When needed, the definitions of these indicators were added directly in the database template.</p> <p>In total, 48 data sets (some of them further divided into sub-sets) were collected. Most of the collected data represent quantitative data in the format of [number], [%] [€] or [km²].</p> <p>The data on urban metabolism received from the pilot cases is stored in 1 excel database.</p> <p> </p> <p><strong>Further Information and Contact</strong></p> <p>The <strong>data </strong>on waste generation and management, socio-economic data and tourism data used for all the assessments performed within Work Package 2 and presented in this report <strong>was provided by the URBANWASTE pilot cases</strong>. More detailed information is contained within the database.</p> <p><strong>In case of questions related to this database please contact: abf@boku.ac.at</strong></p> <p> </p> <p>For more information on the <strong>URBANWASTE </strong>project please visit: http://www.urban-waste.eu/</p>
Data from: "Non-metabolizable" glucose analogue shines new light on priming mechanisms: Triggering of microbial metabolism
<p>Raw data for the article:</p> <p>Kyle Mason-Jones*, Yakov Kuzyakov (2017)<br> “Non-metabolizable” glucose analogue shines new light on priming mechanisms: Triggering of microbial metabolism</p> <p>Soil Biology and Biochemistry 107, 68-76</p> <p>https://doi.org/10.1016/j.soilbio.2016.12.015</p> <p>* corresponding author: kmasonj@gwdg.de</p>
Insights into metabolic changes during epidermal differentiation as revealed by multiphoton microscopy with fluorescence lifetime imaging
<p>Rapid developments in the field of organotypic cultures has generated a growing need for effective quality control measures during tissue development. In this study, we correlate metabolic changes with epidermal differentiation and demonstrate that multiphoton microscopy with fluorescence lifetime imaging (MPM-FLIM) can be applied as a non-invasive approach to monitor epidermal differentiation of keratinocytes with respect to proliferative and differentiated states. Keratinocytes grown at 1.5 mM Ca2+ exhibited increased expression of differentiation markers KRT1 and KRT10 compared to 60 μM Ca2+, and a metabolic shift from glycolysis to mitochondrial respiration. Fitting the fluorescence decay with a biexponential model revealed a decreased relative fraction of intracellular NADH and FAD after high calcium treatment, consistent with increased oxidative phosphorylation. Using these two parameters, the epidermal differentiation process could be monitored over a 96 h period. Implementing discriminating analysis based on k-means clustering generated clusters that correlated well with culturing time, suggesting that this methodology can be employed as part of an automated pipeline for monitoring keratinocyte differentiation.</p>
Interstage single ventricle heart disease infants show dysregulation in multiple metabolic pathways: targeted metabolomics analysis - Data
<p>The data in this Zenodo entry corresponds to the data used to produce the results in <a href="https://www.jacc.org/doi/full/10.1016/j.jacadv.2022.100169">https://www.jacc.org/doi/full/10.1016/j.jacadv.2022.100169</a>. The zipped folder contains three files</p> <ul> <li>Metabolite Data.csv - The meatobilte measurements for all the samples</li> <li>Clinical Data.csv - Values for the clinical variables</li> <li>Clinical Data Descriptions.csv - More in depth explanation of clinical variables as well as possible values of the variables</li> </ul> <p><span>This study was supported by the American Heart Association (AHA</span><span>20CDA35310498 and AHA18IPA34170070) and the National Institutes </span><span>of Health (NIH/NCATS Colorado CTSA, No. UL1 TR001082 and NIH/</span><span>NHLBI K23HL12363</span></p>
Supporting Online Data for 'Timber trade in the United States of America 1870 to 2017. A socio-metabolic analysis'
<p>This data file (.xlsx) contains all data used to create tables and figures of the study "Timber trade in the United States of America 1870 to 2017. A socio-metabolic analysis". Main article is available under: https://doi.org/10.1080/01615440.2024.2316039</p>
EFSA Project on the use of NAMs to explore interspecies metabolic differences on essential oils as feed additives (Annexes A, B, C, D)
<p>Raw data of phase I and II experiments and PBK model input data and simulation of the EFSA Project on the use of NAMs to explore interspecies metabolic differences on essential oils as feed additives (OC/EFSA/SCER/2021/14).</p>
Raw metabolomics data of the paper: New findings in the metabolism of the saffron apocarotenoids, crocins and crocetin, by the human gut microbiota
<p>Raw dataset of the metabolomicas data of the study : New findings in the metabolism of the saffron apocarotenoids, crocins and crocetin, by the human gut microbiota.</p> <p>The csv file contain the raw data matrix exported from MS-DIAL software after total ions aligment across all study samples.</p>
Bone metabolism gene variation and response to bisphosphonate treatment in women with postmenopausal osteoporosis
<p>This repository contains the raw and source data for the manuscript "Bone metabolism gene polymorphism and response to bisphosphonate treatment in women with postmenopausal osteoporosis" submitted to PLOS ONE.</p> <p><strong>Abstract: </strong></p> <p><em>Introduction:</em> Long-term treatment is used in patients with osteoporosis, and bisphosphonates (BPs) are the most commonly prescribed medications. However, in some patients this therapy is not effective, cause different side effects and complications. Unfortunately, at least one year is needed to identify and confirm an ineffectiveness of BPs therapy on bone mineral density (BMD). Among other factors, a response to BPs therapy may also be explained by genetic factors. The aim of this study was to analyze the influence of <em>SOST, PTH, FGF2, FDPS, GGPS1, </em>and<em> LRP5</em> gene polymorphisms on the response to treatment with BPs.</p> <p><em>Materials and methods: </em>Women with postmenopausal osteoporosis were included to this study if they used bisphosphonates for at least 12 months. Exclusion criteria were: persistence on BPs therapy less than 80%, bone metabolic diseases, diseases deemed to affect bone metabolism, malignant tumours, using of any medications influencing BMD. The study protocol was approved by the local ethics committee. The BMD at the lumbar spine and femoral neck were measured using dual x-ray absorptiometry (GE Lunar) before and at least 12 months after treatment with BPs. According to BMD change, patients were divided in two groups – responders and non-responders to BPs terapy. Polymorphic variants in <em>SOST, PTH, FGF2, FDPS, GGPS1, </em>and<em> LRP5</em> genes were determined using PCR analysis with TaqMan probes (Thermo Scientific).</p> <p><em>Results:</em> In total, 201 women with BPs therapy were included in the study. No statistically significant differences were observed in age, age at menopause, weight, height, BMI and baseline BMD levels between responders (122 subjects) and non-responders (79 subjects).</p> <p>As single markers, the <em>SOST </em>rs1234612 T/T (OR=2.3; P=0.02), <em>PTH</em> rs7125774 T/T (OR=2.8, P=0.0009), <em>FDPS</em> rs2297480 G/G (OR=29.3, P=2.2×10<sup>-7</sup>), and <em>GGPS1</em> rs10925503 C/C+C/T (OR=2.9; P=0.003) gene variants were over-represented in non-responders group. No significant association between <em>FGF2</em> rs6854081 and <em>LRP5</em> rs3736228 gene variants and response to BPs treatment was observed. The carriers of T-T-G-C allelic combination (constructed from rs1234612, rs7125774, rs2297480, and rs10925503) were predisposed to negative response to BPs treatment (OR = 4.9, 95% CI 1.7–14.6, P=0.005). The C-C-T-C combination was significantly over-represented in responders (OR = 0.1, 95% CI 0.1–0.5, P=0.006).</p> <p><em>Conclusions:</em> Our findings highlight the importance of identified single gene variants and their allelic combinations for pharmacogenetics of BPs therapy of osteoporosis. Complex screening of these genetic markers could be used as a new strategy for personalized antiresorptive therapy.</p>
Compartment and Hub Definitions Tune Metabolic Networks for Metabolomic Interpretations
<p>This archive contains data for a report by the same title.<br> Data relate to software projects MetaboNet and DyMetaboNet.<br> MetaboNet: https://github.com/tcameronwaller/metabonet<br> DyMetaboNet: https://github.com/tcameronwaller/dymetabonet</p> <p>File descriptions</p> <p>dymetabonet_2019-08-29.mp4 ... raw screen capture video of DyMetaboNet<br> dock_metabonet_2019-08-18.zip ... complete MetaboNet export<br> model_* ... curation of human metabolic model by MetaboNet<br> model_dymetabonet.zip ... format for DyMetaboNet<br> model_compartments* ... compartments<br> model_processes* ... processes<br> model_reactions* ... reactions<br> model_metabolites* ... metabolites<br> measurement_* ... curation of metabolomic measurements by MetaboNet<br> measurement_study_*_report.tsv ... summary of match measurements to metabolites<br> measurement_study_*.tsv ... metabolites' fold changes and probabilities between groups<br> measurement_study_*_metaboanalyst.txt ... format for MetaboAnalyst<br> measurement_study_*_metaboanalyst_pair.txt ... format for MetaboAnalyst with sample pairs<br> network_* ... multiple definitions of metabolic networks<br> network_compartments-true_hubs-true.zip ... compartmental network with hubs<br> network_compartments-true_hubs-false.zip ... compartmental network without hubs<br> network_compartments-false_hubs-true.zip ... noncompartmental network with hubs<br> network_compartments-false_hubs-false.zip ... noncompartmental network without hubs<br> network_compartments-*_hubs_*/network_cytoscape.json ... format for Cytoscape<br> network_compartments-*_hubs_*/network_networkx.pickle ... format for NetworkX<br> network_compartments-*_hubs_*/nodes_reactions.pickle ... network's nodes for reactions<br> network_compartments-*_hubs_*/nodes_metabolites.pickle ... network's nodes for metabolites<br> network_compartments-*_hubs_*/links.pickle ... network's links<br> network_compartments-*_hubs_*/analysis/nodes_reactions.tsv ... nodes' metrics relative to reactions<br> network_compartments-*_hubs_*/analysis/nodes_metabolites.tsv ... nodes' metrics relative to metabolites<br> network_compartments-*_hubs_*/analysis/network_reactions.tsv ... network's metrics relative to reactions<br> network_compartments-*_hubs_*/analysis/network_metabolites.tsv ... network's metrics relative to metabolites<br> network_compartments-*_hubs_*/measurement/metabolites.tsv ... measurements on nodes for metabolites</p>
Common biochemical and topological properties of metabolic genes recurrently dysregulated in tumors
<p>Although tumors exhibit numerous metabolic alterations, it’s unclear if common objectives and constraints underlie diverse metabolic changes. Here we interpret cancer gene expression, copy number variation, and survival data using a computational model, MetOncoFit. MetOncoFit evaluates142 metabolic features that can impact tumor fitness, including enzyme catalytic activity, pathway association, network topological attributes, and reaction flux. Meta-analysis of tumor databases using MetOncoFit revealed that metabolic enzymes with high catalytic activity were frequently up-regulated in many tumors and associated with poor survival. MetOncoFit also identified metabolites that were hot-spots of dysregulation. MetOncoFit illuminates how enzyme activity and metabolic network architecture influences tumorigenesis.</p>
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> </p>
Shape, membrane morphology, and morphodynamic response of metabolically active human mitochondria revealed by scanning ion conductance microscopy
<p>This contains the hole data set as well as all analysed data for the paper published in Beilstein Journal of Nanotechnology "Shape, membrane morphology and morphodynamic response of metabolically active human mitochondria revealed by Scanning Ion Conductance Microscopy".</p> <p>Most of the images were taken with the SICM. These uncompressed tiff files can be read and processed with the Gwyddion software or other scanning probe image processing software.</p>
Supplementary material for "Learning Boolean controls in regulated metabolic networks: a case-study"
<p>This record contains notebooks and Docker image for reproducing the learning of Boolean controls in regulated metabolic networks, and the case study presented in the CMSB 2021 conference proceeding article "Learning Boolean controls in regulated metabolic networks: a case-study".</p> <p>Visualize notebooks online:</p> <ul> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/5060985/files/CaseStudy-Simulations.ipynb">CaseStudy-Simulations.ipynb</a></li> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/5060985/files/CaseStudy-SearchSpace.ipynb">CaseStudy-SearchSpace.ipynb</a></li> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/5060985/files/CaseStudy-Inference.ipynb">CaseStudy-Inference.ipynb</a></li> </ul> <p>Notebooks can be executed interactively within the Docker image <code>bioasp/boolean-caspo-flux:cmsb2021 </code>which extends the <a href="http://colomoto.org/notebook">CoLoMoTo Docker</a> version <code>2021-02-01.</code></p> <p>Alternatively, they can be executed without any installation at <a href="https://mybinder.org/v2/zenodo/10.5281/zenodo.5070151/">https://mybinder.org/v2/zenodo/10.5281/zenodo.5070151/</a>.</p> <p>The Docker image can be executed as follows:</p> <pre><code class="language-bash">docker pull bioasp/boolean-caspo-flux:cmsb2021 docker run -it --rm -p 8888:8888 bioasp/boolean-caspo-flux:cmsb2021 </code></pre> <p>then point your browser to <a href="http://127.0.0.1:8888">http://127.0.0.1:8888</a>.</p> <p>The image can be imported using the command <code>docker load</code> with the image file provided in this record:</p> <pre><code>docker load -i image.tar.gz</code></pre> <p>or with the <code>donodo</code> command available at <a href="https://github.com/pauleve/donodo">https://github.com/pauleve/donodo</a>:</p> <pre><code>pip install -U donodo donodo pull 10.5281/zenodo.5070151</code></pre>
Metabolic shift of chronic myeloid leukemia patients under Imatinib-Pioglitazone regimen and discontinuation_dataset
<p>The EDI-PIO (<strong>E</strong>studo de <strong>D</strong>escontinuação de <strong>I</strong>matinibe após<strong> Pio</strong>glitazona) is a single-center, longitudinal, prospective, phase 2, non-randomized, open, clinical trial (NCT02852486, August 2, 2016 retrospectively registered) for the discontinuation of imatinib after concomitant use of pioglitazone, being the first of its kind in a Brazilian population with chronic myeloid leukemia. Due to remaining of leukemic quiescent cells that are not affected by tyrosine kinase inhibitors, it has been suggested the use of pioglitazone, a PPARγ agonist, together with imatinib as a strategy for the maintenance of deep molecular response. The clinical benefit to this association is still controversial, and the metabolic alteration along this process remains unclear. Therefore, we applied a metabolomic protocol using high-resolution mass spectrometry to profile plasmatic metabolic response of a prospective cohort of 10 individuals under discontinuation of imatinib and pioglitazone protocol. By comparing patients under pioglitazone and imatinib treatment with imatinib monotherapy and discontinuation phase, we were able to annotate 41 and 36 metabolites, respectively. The metabolic alterations observed during Imatinib-Pioglitazone combined therapy are associated with an extensive lipid remodelling, with activation of β-oxidation pathway, in addition to the presence of markers that suggest mitochondrial dysfunction.</p>
Stream metabolism (as resazurin-resorufin transformation) along a boreal headwater stream and its relation to groundwater organic matter supply
<p>Datasets supporting the manuscript entitled "<strong><em>Groundwater-stream connections shape the spatial patterns and rates of aquatic metabolism</em></strong>", published in L<em>imnology and Oceanography Letters</em>. Three datasets are available:</p> <ul> <li>"<em><strong>Groundwater_Characterization.csv":</strong></em> dissolved organic matter characterization of and heterotrophic activity associated with, the major water sources discharging into a headwater boreal stream during summer 2017. Major water sources are: lake water and five discrete groundwater inflows (here named as <em>discrete riparian inflow points)</em>.</li> <li>"<em><strong>Raz_Additions.csv</strong></em>": Constant-rate additions of resazurin performed in a boreal headwater stream (Krycklan catchment, Sweden) during seven dates of summer 2017. Data contains resazurin and resorufin concentrations from the surface and hyporheic water at 18 stations along a 90-m long reach. </li> <li>"<em><strong>Raz_transformation_metric.csv</strong></em>": Hydrologic and metabolic characterization of the 90-m long reach for the seven resazurin additions conducted in summer 2017. </li> </ul> <p>More information about the data can be found in the document "<strong><em>Metadata.doc</em></strong>". Information about field and laboratory procedures can be found in the main manuscript or in the document "<strong><em>Supporting_Information.doc</em></strong>".</p>
Two metabolomics data sets (mouse kidney, mouse plasma), generated for the publication Bignon et al., 2023: "Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock".
<p><strong>Publication: </strong>Bignon Y, Wigger L, Ansermet C, Weger BD, Lagarrigue S, Centeno G, Durussel F, Götz L, Ibberson M, Pradervand S, Quadroni M, Weger M, Amati F, Gachon F, Firsov D. Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock. J Clin Invest. 2023 Mar 2:e167133. doi: 10.1172/JCI167133. Epub ahead of print. PMID: 36862511.</p> <p> </p> <p><strong>Abstract: </strong> Circadian rhythmicity in renal function suggests rhythmic adaptations in renal metabolism. To decipher the role of the circadian clock in renal metabolism, we studied diurnal changes in renal metabolic pathways using integrated transcriptomic, proteomic, and metabolomic analysis performed on control mice and mice with inducible deletion of the circadian clock regulator Bmal1 in the renal tubule (cKOt). With this unique resource, we demonstrated that ~30% RNAs, ~20% proteins and ~20% metabolites are rhythmic in kidneys of control mice. Several key metabolic pathways including NAD+ biosynthesis, fatty acid transport, carnitine shuttle,and b-oxidation displayed impairments in kidneys of cKOt, resulting in a perturbed mitochondrial activity. Carnitine reabsorption from the primary urine was one of the most impacted processes with a ~50% reduction in plasma carnitine levels and a parallel systemic decrease in tissues carnitine content. This suggests that the circadian clock in the renal tubule controls both kidney and systemic physiology.</p> <p> </p> <p><strong>This record contains two separate mass-spectrometry metabolomics data sets associated with this study:</strong></p> <ol> <li>Metabolic profile of renal tubules, MS/MS data, Metabolon, Morrisville, NC (N=60)</li> <li>Metabolic profile of blood plasma, MS/MS data, Biocrates, Innsbruck, Austria (N=60)</li> </ol> <p>For each data set, original data as received from the platforms and processed data as used in the data analysis are provided. Preprocessing of kidney data included removal of metabolites with more than 80% missing data values, median normalization, imputation and glog2 transformation. Preprocessing of plasma data included filtering of metabolites with any missing data and log2 transformation. Details of data processing are available in the STAR*methods of the publication.</p> <p> </p> <p><strong>Data sets in other repositories associated with the same study:</strong></p> <p>Additional data sets (transcriptomics, proteomics) pertaining to the same study have been deposited in public repositories:</p> <ul> <li>Gene Expression Omnibus (NCBI GEO), GSE216252</li> <li>PRIDE Archive (EMBL-EBI), PXD036803</li> </ul> <p> </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.