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Data set for "Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex"
<p>Data set for: Sermet BS, Truschow P, Feyerabend M, Mayrhofer JM, Oram TB, Yizhar O, Staiger JF, Petersen CCH (2019) Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex. eLife 8: e52665. https://doi.org/10.7554/eLife.52665</p> <p>There are 2 files in this upload:</p> <p>1. The file named "2019_Sermet_eLife.pdf" is the Open Access pdf file of the manuscript published in eLife.</p> <p>2. The file named "Sermet_data_code.zip" (~5 GB) is a zipped version of a folder "Sermet_data_code" (~5 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. When unzipped, the folder contains 8 Matlab '.m' files with analysis code and one '.mat' data file. In order to run the analysis of the data set, you need to execute 'PopPlot.m'.</p>
Data_text section 3.3_Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2
<p>Data from kinetic characterization (Km and vmaxapp) described in text section 3.3 of Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2</p> <p>Dataset (doi:<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>) contains values from kinetic characterization (10.1016_j.jsbmb.2019.03.011_text3.3_Km_vmax) described in text section 3.3 corresponding to raw data obtained from LC-MS/MS analysis provided as three files in CSV format (31003A-179400_date_name_25Oxysterol_4_10_1-3). All further experiment related information and subsequent data analysis provided as two meta-data-files: (31003A-179400_date_name_25Oxysterol_4_9_M_1-2) as TXT and pdf format.</p>
Data_Figure 2_Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2
<p>Data of figure 2 from Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2</p> <p>Dataset (doi:<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>) contains the original figure in PNG format, (<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>_Fig. 2). Corresponding raw data obtained from LC-MS/MS analysis provided as eight files in CSV format (31003A-179400_Date_Name_25Oxysterol_4_Dataset_1-4). All further experiment related information and subsequent data analysis provided as two meta-data-files (31003A-179400_Date_Name_25Oxysterol_4_Dataset _M_1-2) as TXT format and PDF format.</p>
Data_Figure 4_Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2
<p>Data of figure 4 from Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2</p> <p>Dataset ((doi:<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>) contains the original figure as PNG format (<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>_Fig. 4). Corresponding raw data obtained from liquid scintillation analysis provided as 10 files in CSV format (31003A-179400_date_KB_25Oxysterol_11_dataset_1-4). All further experiment related information and subsequent data analysis provided as three meta-data-files (31003A-179400_date_name_25Oxysterol_11_dataset_M_1) as TXT format.</p>
Data_Figure 1_Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2
<p>Data of figure 1 from Enzymatic interconversion of the oxysterols 7β,25 dihydroxycholesterol and 7-keto,25-hydroxycholesterol by 11β-hydroxysteroid dehydrogenase type 1 and 2</p> <p>Dataset (doi:<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>) contains the original figure as PNG format (<a href="https://doi.org/10.1016/j.jsbmb.2019.03.011">10.1016/j.jsbmb.2019.03.011</a>_Fig. 1). Corresponding raw data obtained from LC-MS/MS analysis provided six files in CSV format (31003A-179400_Date_Name_25Oxysterol_4_Dataset _1-3). All further experiment related information and subsequent data analysis provided as two meta-data-files (31003A-179400_Date_Name_25Oxysterol_4_Dataset_M_1-2) as TXT format and PDF format</p>
Data from : Classifying wetland‐related land cover types and habitats using fine‐scale lidar metrics derived from country‐wide Airborne Laser Scanning
<p>This data repository contains the processed lidar metrics for characterizing the habitat structure for classifying main land cover and habitat types in the Lauwersmeer area in the northern part of the Netherlands in the province of Groningen (5754 ha). The lidar metrics were derived from Airborne Laser Scanning (ALS) data using the Actueel Hoogtebestand Nederland 2 (AHN2) openly available dataset from https://www.pdok.nl/. </p> <p>The derived lidar metrics saved in *.grd file format and contain 32 bands. Each band represents a lidar metric and the water surface was masked out in the dataset. The *l1* in the file name indicates that the file was used for level 1 (wetland) classification and *l23* used for level 2 (land cover types within wetland) and level 3 (reedbed habitats) classification. The lidar metrics were calculated using lidR (<a href="https://github.com/Jean-Romain/lidR">https://github.com/Jean-Romain/lidR</a>) software package. Further details related to the lidar metrics extraction can be found at <a href="https://github.com/eEcoLiDAR/PhDPaper1_Classifying_wetland_habitats">https://github.com/eEcoLiDAR/PhDPaper1_Classifying_wetland_habitats</a> Github repository.</p> <p> </p>
Raw data used for COI delineation of the Eupolybothrus species: Authors: Stoev et al. 2013 Data type: genomic The archive contains the following data: 1) fasta-Alignment as the basis for all analyses (.FASTA), 2) mega-file for the calculation of the genetic distances and the NJ tree (.MDSX), 3) NJ-tree in Newick format (.NWK), 4) graph of the TCS Software for the Statistical Parsimony method (.GRAPH) File: E_cavernicolus.rar from: Eupolybothrus cavernicolus Komerički & Stoev sp. n. (Chilopoda: Lithobiomorpha: Lithobiidae): the first eukaryotic species description combining transcriptomic, DNA barcoding and micro-CT imaging data - Biodiversity Data Journal 1: e1013 (28 October 2013) https://doi.org/10.3897/BDJ.1.e1013
<p>Authors: Stoev et al. 2013 Data type: genomic The archive contains the following data: 1) fasta-Alignment as the basis for all analyses (.FASTA), 2) mega-file for the calculation of the genetic distances and the NJ tree (.MDSX), 3) NJ-tree in Newick format (.NWK), 4) graph of the TCS Software for the Statistical Parsimony method (.GRAPH) File: E_cavernicolus.rar</p>
Data collection for Tsuji et al., 2023, Anoxygenic phototrophic Chloroflexota member uses a Type I reaction center
<p>Supplementary data files associated with Tsuji et al., 2023, "Anoxygenic phototrophic <i>Chloroflexota</i> member uses a Type I reaction center". These files are used by code in a corresponding GitHub repository (<a href="https://github.com/jmtsuji/Ca-Chlorohelix-allophototropha-RCI">https://github.com/jmtsuji/Ca-Chlorohelix-allophototropha-RCI</a>) that shows how various analyses that are presented in the paper were conducted.</p><p>Files included:</p><ul><li>HPLC-based spectroscopy data ("...-HPLC-run1.tsv.gz" or "...-HPLC-run2.tsv.gz") -- hyper-spectral data files, generated by a diode array detector, that are associated with pigment analyses in the paper. See the corresponding Github repo for how these files are analyzed.</li><li>Supplementary data about "<i>Ca. </i>Chloroheliales"-associated RCI:<ul><li>I_TASSER_homology_models_full_output.tar.gz -- Gzipped tarball containing the full output from I-TASSER for homology models of key phototrophy-related genes encoded by '<i>Candidatus </i>Chlorohelix allophototropha' and '<i>Candidatus </i>Chloroheliales bin L227-5C'. After unpacking the tarball, view a summary of the I-TASSER output for each gene by clicking on the 'index.html' file in that gene's folder.</li></ul></li><li>Boreal Shield lake survey data:<ul><li>lake_survey_MAGs.tar.gz -- Gzipped tarball containing the full collection of 756 metagenome-assembled genomes (MAGs) recovered from the Boreal Shield lake survey, corresponding to those mentioned in Supplementary Data 3. The FastA nucleotide genome sequences, FastA nucleotide predicted protein-coding gene sequences, FastA amino acid predicted protein sequences, and Genome Flat Files (GFFs) for all genomes are provided in the fna, ffn, faa, and gff subdirectories, respectively.</li><li>lake_survey_MAGs_eggnog_annotations.tar.gz -- Gzipped tarball containing annotations (produced via EggNOG) for all predicted proteins among the 756 MAGs recovered from lake metagenome data. Because proteins were pre-clustered prior to annotation, a "orf2gene" file inside the tarball maps the gene clusters to the ORF IDs used for each genome.</li><li>lake_survey_MAGs_featureCounts.tsv.gz -- GZipped tab-separated table containing the mapping statistics of metatranscriptome reads on all protein-coding genes from the 756 MAGs recovered from lake metagenome data.</li><li>lake_survey_Ca_Chloroheliales_MAGs_info.tar.gz -- A subset of information from the previous three files specific to genome bins ELA319 and ELA729, which represent RCI-encoding "<i>Ca</i>. Chloroheliales" members.</li></ul></li><li>Intermediate files involved in some of the genome assembly work in this paper:<ul><li>Capt_S15_sequencer_data_raw.tar.gz -- Gzipped tarball containing the raw Illumina MiSeq output data for the '<i>Candidatus </i>Chlorohelix allophototropha' subculture 15 sequencing run. The run represents a read cloud sequencing run relying on TELL-Seq technology. Indices can be parsed directly from raw output data using the Tell-Read pipeline.</li><li>scaffold.full.fasta.gz -- the assembled scaffolds generated using Tell-Read and Tell-Link on the above raw MiSeq output data.</li><li>Ca_Chloroheliaceae_bin_L227_5C_prokka_ORFs.faa.gz -- predicted open reading frames (ORFs) from the curated genome of '<i>Candidatus </i>Chloroheliales bin L227-5C'. These ORFs were predicted using prokka and were used for some of the analyses presented in the paper. Most analyses used the annotations available on NCBI (generated by PGAP) for this strain.</li></ul></li></ul>
Processed data to accompany "Clonally heritable gene expression imparts a layer of diversity within cell types"
<p>This is the processed data underlying the paper "Clonally heritable gene expression imparts a layer of diversity within cell types" by Mold, Weissman, et al. Data has been gone through preprocessing steps, using the Python Notebooks found at <a href="https://github.com/MartyWeissman/ClonalOmics/tree/main/Data">https://github.com/MartyWeissman/ClonalOmics/tree/main/Data</a>. </p> <p>Smaller files are provided in .csv (comma-separated-value) format and larger files such as expression matrices are provided in .loom format (<a href="https://anndata.readthedocs.io/en/latest/">using the AnnData package</a>).</p> <p> </p> <p> </p>
Raw differential gene expression data, data S1, from: Molecular cascades and cell type-specific signatures in ASD revealed by single cell genomics
<p>Genomic profiling in post-mortem brain from autistic individuals has consistently revealed convergent molecular changes. What drives these changes and how they relate to genetic susceptibility in this complex condition is not understood. We performed deep single nuclear RNA sequencing (snRNAseq) to examine cell composition and transcriptomics, identifying dysregulation of cell type-specific gene regulatory networks (GRNs) in autism, which we corroborated using snATAC-seq and spatial transcriptomics. Transcriptomic changes were primarily cell type-specific, involving multiple cell types, most prominently interhemispheric and callosal-projecting neurons, interneurons within superficial laminae, and distinct glial reactive states involving oligodendrocytes, microglia, and astrocytes. Autism-associated GRN drivers and their targets were enriched in rare and common genetic risk variants, connecting autism genetic susceptibility and cellular and circuit alterations in the human brain. This data is the raw differential gene expression comparing ASD versus CTL subjects for each cell cluster. </p>
Sexual dimorphism in subterranean amphipod crustaceans covaries with subterranean habitat type: data and R code
<p>The data and R code used for data analyses in the manuscript titled "Sexual dimorphism in <em>Niphargus </em>amphipods is predicted by surface-subterranean environmental gradient". The collection contains:</p> <ol> <li>A zipped folder "videos", where raw videos used in the study are stored.</li> <li>A zipped folder "tracking_results", where video-tracking results obtained from the raw videos are stored, along with supporting files and R code (Rscript_extract_behavior.Rmd) with custom functions (Behavior_custom_functions.Rmd) needed to analyze tracking results and retrieve final behavioral data.</li> <li>A README file with details on how the data and code is organized.</li> <li>Supplementary Material file including all raw data used in the main data analysis (SupplementaryMaterial.xlsx)</li> <li>A supporting file with data from another study used in the main data analysis (sex_ratio.xlsx, results from https://onlinelibrary.wiley.com/doi/full/10.1111/jeb.13917; https://zenodo.org/records/5175861)</li> <li>Two files containing phylogenetic trees: one complete phylogenetic tree of<em> Niphargus </em>(consensus_tree)<em> </em>and 100 randomly drawn phylogenetic trees from the stationary phase of the Bayesian analysis, pruned to focal species (100_pruned_trees), which were used in the main data analysis.</li> <li>The Rcode containing the code of the main data analysis to reproduce the reported results (RScript_data_analysis.Rmd), as well as some additional analyses not included in the manuscript.</li> </ol>
Data from: Seed preference is only weakly linked to seed-type-specific feeding performance in a songbird
<p>The dehusking of seeds by granivorous songbirds is a complex process that requires fast, coordinated and sensory-feedback-controlled movements of beak and tongue. Hence, efficient seed handling requires a high degree of sensorimotoric skill and behavioural flexibility, since seeds vary considerably in size, shape and husk structure. To deal with this variability, individuals might specialise on specific seed types, which could result in greater seed handling efficiency of the preferred seed type, but lower efficiency for other seed types. To test this, we assessed seed preferences of canaries (Serinus canaria) through food choice experiments and related these to data of feeding performance, seed handling skills and beak kinematics during feeding on small, spindle-shaped canary seeds and larger, spheroid-shaped hemp seeds. We found great variety in seed preferences among individuals: some had no clear preference, while others almost exclusively fed on hemp seeds, or even prioritized novel seed types (millet seed). Surprisingly, we only observed few and weak effects of seed preference on feeding efficiency. This suggests that either the ability to handle seeds efficiently can be readily applied across various seed types, or alternatively, it may indicate that achieving high levels of seed-specific handling skills does not require extensive practice.</p>
Data for Identifying Knot Types of Polymer Conformations by Machine Learning
<h1>Training Data and Generalizability Testsets</h1> <h2>For the publication PhysRevE.101.022502</h2> <pre>@article{PhysRevE.101.022502, title = {Identifying knot types of polymer conformations by machine learning}, author = {Vandans, Olafs and Yang, Kaiyuan and Wu, Zhongtao and Dai, Liang}, journal = {Phys. Rev. E}, volume = {101}, issue = {2}, pages = {022502}, numpages = {10}, year = {2020}, month = {Feb}, publisher = {American Physical Society}, doi = {10.1103/PhysRevE.101.022502}, url = {https://link.aps.org/doi/10.1103/PhysRevE.101.022502} }</pre> <h2>GitHub source code demo using this dataset: </h2> <p><a href="https://github.com/CompSoftMatterBiophysics-CityU-HK/Identify-Knot-Types-by-ML-PRE2020"><strong>🥨 https://github.com/CompSoftMatterBiophysics-CityU-HK/Identify-Knot-Types-by-ML-PRE2020</strong></a></p> <p><strong>The above GitHub repo provide <strong>a docker, training code, best model with weights, and two showcases of generalizability</strong>.</strong></p>
Datasets for CASSL: A cell-type annotation method for single cell transcriptomics data using semi-supervised learning
<p>This repository contains datasets used in the project CASSL: A cell-type annotation method for single cell transcriptomics data using semi-supervised learning. This project aims at learning cell annotations for missing cell labels via NMF and recursive k-Means clustering.</p>
Data for: Trap type affects dung beetle taxonomic and functional diversity in Bornean tropical forests
<p>Dung beetle community composition data. Data was collected using either dung-baited pitfall traps or flight interception traps. Each row represents one trap, with the author/study information, name of study site, sampling period, trap type and habitat type. Dung beetle species and their abundances are listed. See "metadata" tab for more details.</p> <p>Paper abstract: Baited pitfall traps (BPTs) and flight intercept traps (FITs) are the most common methods employed for sampling dung beetle communities. These methods vary in their efficacy and are affected by factors such as the bait types used and the dispersal abilities of different dung beetle species. We present the first quantitative comparison of the taxonomic and functional diversity, and community composition of dung beetles caught in BPTs and FITs in Bornean tropical forests. We show that BPTs and FITs captured complementary communities with different functional traits, and that BPTs captured more functionally diverse communities. We therefore recommend using a combination of both baited BPTs and FITs for studies assessing the composition of dung beetles across habitat types. Our results also highlight that it is important to consider how trap type affects the trait composition of communities when relating dung beetle communities and functional traits to ecological functioning. We suggest modifications to FITs based on the design of harp traps to increase their effectiveness in capturing larger-bodied beetles.</p>
NMR data of Lanostane Type Triterpenoids isolated from Leplaea mayombensis
<p>This folder contains NMR datasets of new compounds described in the publication<em> </em>entitled: <strong>Antiplasmodial and Cytotoxic Activity of Lanostane Type Triterpenoids isolated from <em>Leplaea mayombensis</em></strong></p> <p> </p> <p>NMR processing : Topspin 4.1.13</p> <p> </p>
CSV files and R script: writing process data of typed picture description by 15 cognitively impaired patients and 15 healthy controls
<p>Writing process data of 15 cognitively impaired patients and 15 age- and gender-matched healthy controls were obtained. Each of them completed two typed picture description tasks that were logged with Inputlog, a keystroke logging tool. Variables included time on task; number of characters, pauses and Pause-bursts per minute; proportion of pause time; duration of Pause-bursts; and pause time between words. For pause time between words, also the effect of pauses preceeding specific word categories was analyzed.</p> <p>The data were used to explore if the observation of writing behavior can assist in the screening and follow-up of mild cognitive impairment (MCI) and mild dementia due to Alzheimer’s disease (AD). This data set contains the CSV files that were used for the analyses and the corresponding R script.</p>
Data from: Landscape diversity and local temperature, but not climate, affect arthropod predation among habitat types
<p>Arthropod predators are relevant for top-down regulation of insect herbivores. Biotic and abiotic factors influence predator communities and their activity with consequences for the strength of top-down regulation ('arthropod predation'). Anthropogenic climate and land-use change urges a deeper understanding of the combined effects of potential drivers on arthropod predation. This study obtained arthropod predation rates on 113 plots of open herbaceous vegetation adjacent to different habitat types (forest, grassland, arable field, settlement) along climate and land-use gradients in Bavaria, Germany, using a standardized method of artificial caterpillars at ground level. Predation rates were analysed with regard to habitat characteristics (habitat type, plant species richness, local mean temperature and mean relative humidity during artificial caterpillar exposure), landscape diversity (0.5–3.0-km, six scales), climate (multi-annual mean temperature, 'MAT') and interactive effects of habitat type with other drivers. Arthropod predation rates did not substantially differ between the studied habitat types, related to plant species richness and across the Bavarian-wide climatic temperature gradient, and also no interactive effects were observed. However, arthropod predation rates were limited by low local mean temperatures, tended to decrease towards higher relative humidity and increased towards more diverse landscapes at a 2-km scale. Thus, high arthropod predation rates in open herbaceous vegetation are favoured by diverse landscapes independent of the dominant habitat in the vicinity. Diversifying landscapes may help to improve top-down control of herbivores, e.g. agricultural pests, but more research is needed to derive specific recommendations on landscape management. Little influence of MAT on predation rates suggests that moderate increases of MAT may not strongly alter this process in the near future.</p>
Data from: eDNA metabarcoding of log hollow sediments and soils highlights the importance of substrate type, frequency of sampling and animal size, for vertebrate species detection
<p>Fauna monitoring often relies on visual monitoring techniques such as camera trappings, which have biases leading to underestimates of vertebrate species diversity. Environmental DNA (eDNA) has emerged as a new source of biodiversity data that may improve biomonitoring; however, eDNA based assessments of species richness remain relatively untested in terrestrial environments. We investigated the suitability of fallen log hollow sediment as a source of vertebrate eDNA, across two sites in south-western Australia - one with a Mediterranean climate and the other semi-arid. We compared two different approaches (camera trapping and eDNA metabarcoding) for monitoring of vertebrate species, and investigated the effect of other factors (frequency of species, timing of visits, frequency of sampling, body size) on vertebrate species detectability. Metabarcoding of hollow sediments resulted in the detection of higher species richness in comparison Hollow sediment detected higher species richness (29 taxa: six birds, three reptiles and 20 mammals) to metabarcoding of soil at the entrance of the hollow (13 taxa: three birds, two reptiles and eight mammals). We detected 31 taxa in total with eDNA metabarcoding and 47 with camera traps, with 14 taxa detected by both (12 mammals and two birds). By comparing camera trap data with eDNA read abundance, we were able to detect vertebrates through eDNA metabarcoding that had visited the area up to two months prior to sample collection. Larger animals were more likely to be detected, and so were vertebrates that were identified multiple times in the camera traps. These findings demonstrate the importance of substrate selection, frequency of sampling, and animal size, on eDNA based monitoring. Future eDNA experimental design should consider all these factors as they affect detection of target taxa. </p>
Camera trap data suggest uneven predation risk across vegetation types in a mixed farmland landscape
<p>Ground-nesting farmland birds such as the grey partridge (<em>Perdix perdix</em>) have been rapidly declining due to a combination of habitat loss, food shortage and predation. Predator activity is the least understood factor, especially its modulation by landscape composition and complexity. An important question is whether agri-environment schemes such as flower strips are potentially useful for reducing predation risk, e.g., from red fox (<em>Vulpes vulpes</em>). We employed 120 camera traps for two summers in an agricultural landscape in Central Germany to record predator activity (i.e., the number of predator captures) as a proxy for predation risk and used generalized linear mixed models (GLMMs) to investigate how the surrounding landscape affects predator activity in different vegetation types (flower strips, hedges, field margins, winter cereal and rapeseed fields). Additionally, we used 48 cameras to study the distribution of predator captures within flower strips. Vegetation type was the most important factor determining the number of predator captures and captures rates in flower strips were lower than in hedges or field margins. Red fox capture rates were the highest of all predators in every vegetation type, confirming their importance as a predator for ground-nesting birds. The number of fox captures increased with woodland area and decreased with structural richness and distance to settlements. In flower strips, capture rates in the centre were approximately 9 times lower than at the edge. We conclude that the optimal landscape for ground-nesting farmland birds seems to be open farmland with broad extensive vegetation elements and a high structural richness. Broad flower blocks provide valuable, comparatively safe nesting habitats and the predation risk can further be minimized by placing them away from woods and settlements. Our results suggest that adequate landscape management may reduce predation pressure. </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.