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5,145 results for “CO₂”
MTEX example EBSD map of WC-Co for TrueEBSD and WC Contiguity calculation
<p>MTEX TrueEBSD example EBSD map and SEM images of a WC-Co hardmetal.</p> <p>EBSD data acquired at Seco Tools AB, Fagersta, Sweden.</p> <p>This work was partially funded by the National Physical Laboratory’s Director’s Science and Engineering Fund.</p>
Co-GWAS unveils the genetic architecture of inter-individual epistasis affecting biomass and disease severity in wheat binary mixtures
<p>The repository contains all the data and scripts required to perform the analysis and generate the figures and tables presented in the article: <br>"Co-GWAS unveils the genetic architecture of inter-individual epistasis affecting biomass and disease severity in wheat binary mixtures".</p> <p>0. DATA</p> <p>FOLDER: 0_Data<br>This folder contains the raw phenotypic and genotypic data.</p> <p>I. FILE PREPARATION</p> <p>FOLDER: 1_FilePrep_Design_Fig<br>The R script prepares the phenotypic and genotypic data for analysis and generates the kinship matrix. It also creates a figure illustrating the pairs of phenotyped genotypes.</p> <p>II. PHENOTYPIC ANALYSIS </p> <p>FOLDER: 2_GeneticEffects_PhenoCorr_Residus<br>The R script tests the significance of genetic effects, calculates the proportion of phenotypic variance explained for each phenotype, and checks for correlations between phenotypes. It also controls the residuals in the models.</p> <p>III. A. DGE-BASED GWAS</p> <p>FOLDER: 3_DGE_GWAS<br>This folder contains three subfolders for each phenotype (GWAS_DGE_B, GWAS_DGE_N, GWAS_DGE_P).<br>For example, the pycnidia folder contains the script 3.A_GWAS_DGE_P_AsREML_cluster.R, which performs DGE-based GWAS for the pycnidia phenotype.</p> <p>III. B. Analysis of GWAS Results for DGE</p> <p>FOLDER: 3_DGE_GWAS<br>Within the same folder, the script 3.B_Results_GWAS_DGE_P.Rmd combines the result files and produces Manhattan plots and plots of significant SNPs.</p> <p>IV. A. IGE-BASED GWAS</p> <p>FOLDER: 4_IGE_GWAS<br>This folder contains three subfolders for each phenotype (GWAS_IGE_B, GWAS_IGE_N, GWAS_IGE_P).<br>For example, the pycnidia folder contains the script 4.A_GWAS_IGE_P_AsREML_cluster.R, which performs IGE-based GWAS for the pycnidia phenotype.</p> <p>IV. B. Analysis of GWAS Results for IGE</p> <p>FOLDER: 4_IGE_GWAS<br>Within the same folder, the script 4.B_Results_GWAS_IGE_P.Rmd combines the result files and produces Manhattan plots and plots of significant SNPs.</p> <p>V. PREPARATION OF FILES FOR CO-GWAS</p> <p>FOLDER: 5_FilePrep_coGWAS<br>The script 5.A_FilePrep_coGWAS.Rmd prepares the phenotypic and genotypic data for analysis after SNP pruning.<br>The script 5.B_FilePrep_SNP_Pruning.R performs SNP pruning.<br>The script 5.C_Plot_SNP_Pruning_position.R plots the positions of SNPs before and after pruning.</p> <p>VI. CO-GWAS</p> <p>FOLDER: 6_coGWAS<br>This folder contains three subfolders for each phenotype (coGWAS_B, coGWAS_N, and coGWAS_P). <br>For example, the pycnidia folder contains the script 6.A_coGWAS_DGEIGE_P_Sommer_cluster.R, which performs the co-GWAS for the pycnidia phenotype.<br>The other scripts in this folder combine the result files.</p> <p>VII. HEATMAPS AND QQPLOT OF CO-GWAS RESULTS</p> <p>FOLDER: 7_Heatmaps_qqplots_coGWAS<br>This folder contains three subfolders for each phenotype (Heatmaps_qqplots_B, Heatmaps_qqplots_N, and Heatmaps_qqplots_P).<br>For example, the pycnidia subfolder includes two scripts: 7.A_coGWAS_P_Heatmaps.R generates heatmaps for the pycnidia phenotype and 7.B_coGWAS_P_qqplots.R produces the QQ plot.</p> <p>VIII. BOXPLOTS - 3D PLOTS - PHYSICAL MAPS</p> <p>FOLDER: 8_3Dplots_PhysicalMaps_Boxplots_coGWAS<br>This folder contains three subfolders for each phenotype (Boxplots_PhysicalMaps_3Dplots_B, Boxplots_PhysicalMaps_3Dplots_N, and Boxplots_PhysicalMaps_3Dplots_P).<br>For example, the pycnidia folder contains the script 8_coGWAS_P_Boxplots_PhysicalMaps_3Dplots.R, which generates 3D plots, boxplots and physical maps for the significant interactions. </p> <p>IX. CIRCULAR PLOTS </p> <p>FOLDER: 9_CircularPlots_coGWAS<br>This folder contains three subfolders for each phenotype (CircularPlots_B, CircularPlots_N, and CircularPlots_P).<br>For example, the pycnidia folder contains the script 9_coGWAS_P_CircularPlot.R, which generates the necessary files to create the circular plot. <br>The script circos.conf creates the circular plot. </p> <p>X. GO ENRICHMENT ANALYSIS </p> <p>FOLDER: 10_GOterms_coGWAS<br>This folder contains three subfolders for each phenotype (GOenrichments_B, GOenrichments_N, and GOenrichments_P).<br>For example, the pycnidia folder contains the script 10_coGWAS_P_GOenrichments.Rmd, which generates GO enrichment plots.</p>
Techno-economic comparison of power-to-Ammonia and biomass- to-Ammonia plants using electrolyzer, CO 2 capture and water-gas- shift membrane reactor
<p>A set of imput data used for the paper entitled: Techno-economic comparison of power-to-Ammonia and biomass-<br>to-Ammonia plants using electrolyzer, CO 2 capture and water-gas-shift membrane reactor </p>
Single-molecule analysis of transcription activation: dynamics of SAGA co-activator recruitment
<p>Source data for:</p> <p><strong>Single-molecule analysis of transcription activation: dynamics of SAGA co-activator recruitment</strong></p> <p><strong> </strong></p> <p>Jongcheol Jeon<sup>1</sup>, Larry J. Friedman<sup>2</sup>, Daniel H. Zhou<sup>2</sup>, Hogyu David Seo<sup>1</sup>, Oluwatobi A. Adeleke<sup>3</sup>, Bria Graham<sup>3</sup>, Emily F. Patteson<sup>3</sup>, Jeff Gelles<sup>2</sup>*, and Stephen Buratowski<sup>1,</sup>*</p> <p> </p> <p><sup>1</sup>Department of Biological Chemistry and Molecular Pharmacology,</p> <p>Harvard Medical School, Boston, MA 02115</p> <p><sup>2</sup> Department of Biochemistry, Brandeis University, Waltham, MA 02454</p> <p><sup>3</sup> EpiCypher Inc., Durham NC 27709</p> <p> </p> <p>*Corresponding authors</p> <p>Lead author contact information:</p> <p><a href="mailto:steveb@hms.harvard.edu">steveb@hms.harvard.edu</a></p> <p> </p> <p> </p> <p>The source data for the single molecule experiments are provided as "intervals" files and "CoSMoS parameters", which can be read and manipulated using the publicly available programs "Imscroll" and "Tapqir", respectively:</p> <p><a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a></p> <p><a href="https://github.com/gelles-brandeis/tapqir">https://github.com/gelles-brandeis/tapqir</a></p>
Meta-analysis of scRNA-seq Co-expression in Human Neural Organoids Reveals High Variability in Recapitulating Primary Tissue
<p>Contains all code and data for Werner and Gillis, Meta-analysis of scRNA-seq Co-expression in Human Neural Organoids Reveals High Variability in Recapitulating Primary Tissue, 2024. </p> <p>Additionally, the code and data for this paper can be found at https://github.com/JonathanMWerner/meta_organoid_analysis with an easy to view github markdown file containing all the code used to generate all figure panel plots at https://github.com/JonathanMWerner/meta_organoid_analysis/blob/main/figure_plots_with_data_code.md.</p> <p>Due to file size limits on github, there are several data files not available on github, but are available here on zenodo in the data_for_plots.zip file, see below:</p> <pre>umap_embeddings_Fig2A.Rdata<br>cross_dataset_aggregated_exp_metaMarker_all_fetal_SuppFig1B_Fig2E.Rdata<br>organoid_egad_results_ranked_6_26_24_Fig3D.Rdata<br>fetal_egad_results_ranked_6_26_24_Fig3D.Rdata<br>org_eigenvec_matrices_SuppFig3CD.Rdata</pre> <p><br>The R package developed for this paper is available at https://github.com/JonathanMWerner/preservedCoexp</p>
Data from: Genetic co-structure in a meta-community under threat of habitat fragmentation
Habitat fragmentation increasingly threatens the services provided by natural communities and ecosystem worldwide. An understanding of the eco-evolutionary processes underlying fragmentation-compromised communities in natural settings is lacking, yet critical to realistic and sustainable conservation. Through integrating the multivariate genetic, biotic and abiotic facets of a natural community module experiencing various degrees of habitat fragmentation, we provide unique insights into the processes underlying community functioning in real, natural conditions. The focal community module comprises a parasitic butterfly of conservation concern, and its two obligatory host species, a plant and an ant. We show that both historical dispersal and ongoing habitat fragmentation shape population genetic diversity of the butterfly Phengaris alcon and its most limited host species (the plant Gentiana pneumonanthe). Genetic structure of the individual species was strongly driven by geographical structure, altitude and landscape connectivity. Strikingly, however, was the strong degree of genetic co-structure among the three species that could not be explained by the spatial variables under study. This finding suggests that factors other than spatial configuration, including co-evolutionary dynamics and shared dispersal pathways, cause parallel genetic structure among interacting species. While the exact contribution of coevolution and shared dispersal routes on the genetic variation within and among communities deserves further attention, our findings demonstrate a considerable degree of genetic parallelism in natural meta-communities. The significant effect of landscape connectivity on the genetic diversity and structure of the butterfly also suggests that habitat fragmentation may threaten the functioning of the community module on the long run.
Data from: Seeing is believing? comparing plant-herbivore networks constructed by field co-occurrence and DNA barcoding methods for gaining insights into network structures
Plant-herbivore interaction networks provide information about community organization. Two methods are currently used to document pairwise interactions among plants and insect herbivores. One is the traditional method that collects plant-herbivore interaction data by field observation of insect occurrence on host plants. The other is the increasing application of newly developed molecular techniques based on DNA barcodes to the analysis of gut contents. The second method is more appealing because it documents realized interactions. To construct complete networks, each technique of network construction is urgent to be assessed. We addressed this question by comparing the effectiveness and reliability of the two methods in constructing plant-Lepidoptera larval network in a 50 ha subtropical forest in China. Our results showed that the accuracy of diet identification by observation method increased with the number of observed insect occurrences on food plants. In contrast, the molecular method using three plant DNA markers were able to identify food residues for 35.6% larvae and correctly resolved 77.3% plant (diet) species. Network analysis showed molecular networks had three-fold more unique host plant species but fewer links than the traditional networks had. The molecular method detected plants that were not sampled by the traditional method, e.g., bamboos, bryophytes and lianas in the diets of insect herbivores. The two networks also possessed significantly different structural properties. Our study indicates the traditional observation of co-occurrence is inadequate, while molecular method can provide higher species resolution of ecological interactions.
Data from: Assessing niche partitioning of co-occurring sibling bat species by DNA metabarcoding
Niche partitioning through foraging is a mechanism likely involved in facilitating the coexistence of ecologically similar and co-occurring animal species by separating their use of resources. Yet, this mechanism is not well understood in flying insectivorous animals. This is particularly true of bats, where many ecologically similar or cryptic species coexist. The detailed analysis of the foraging niche in sympatric, cryptic sibling species provides an excellent framework to disentangle the role of specific niche factors likely involved in facilitating coexistence. We used DNA metabarcoding to determine the prey species consumed by a population of sympatric sibling Rhinolophus euryale and R. mehelyi whose use of habitat in both sympatric and allopatric ranges has been well established through radio tracking. Although some subtle dietary differences exist in prey species composition, the diet of both bats greatly overlapped (Ojk = 0.83) due to the consumption of the same common and widespread moths. Those dietary differences we did detect might be related to divergences in prey availabilities among foraging habitats, which prior radio tracking on the same population showed are differentially used and selected when both species co-occur. This minor dietary segregation in sympatry may be the result of foraging on the same prey-types and could contribute to reduce potential competitive interactions (e.g. for prey, acoustic space). Our results highlight the need to evaluate the spatial niche dimension in mediating the co-occurrence of similar insectivorous bat species, a niche factor likely involved in processes of bat species coexistence.
Data from: Pathogen burden, co-infection and major histocompatibility complex variability in the European badger (Meles meles)
Pathogen-mediated selection is thought to maintain the extreme diversity in the major histocompatibility complex (MHC) genes, operating through the heterozygote advantage, rare-allele advantage and fluctuating selection mechanisms. Heterozygote advantage (i.e., recognizing and binding a wider range of antigens than homozygotes) is expected to be more detectable when multiple pathogens are considered simultaneously. Here, we test if MHC diversity in a wild population of European badgers (Meles meles) is driven by pathogen-mediated selection. We examined individual prevalence (infected or not), infection intensity and co-infection of 13 pathogens from a range of taxa, and examined their relationships with MHC class I and class II variability. This population has a variable, but relatively low, number of MHC alleles and is infected by a variety of naturally-occurring pathogens, making it very suitable for the investigation of MHC-pathogen relationships. We found associations between pathogen infections and specific MHC haplotypes and alleles. Co-infection status was not correlated with MHC heterozygosity, but there was evidence of heterozygote advantage against individual pathogen infections. This suggests that rare-allele advantages and/or fluctuating selection, as well as heterozygote advantage are likely to be the selective forces shaping MHC diversity in this species. We show stronger evidence for MHC-associations with infection intensity than for prevalence, and conclude that examining both pathogen prevalence and infection intensity is important. Moreover, examination of a large number and diversity of pathogens, and both MHC class I and II genes (which have different functions), provide an improved understanding of the mechanisms driving MHC diversity.
FIGURE 4 in Co-authorship networks (and other contextual factors) behind the growth of taxonomy of South American Ephemeroptera: A scientometric approach
FIGURE 4. Barplot showing the production of South American authors, including collaborative works. Production measured as number of valid species described.
FIGURE 3 in Co-authorship networks (and other contextual factors) behind the growth of taxonomy of South American Ephemeroptera: A scientometric approach
FIGURE 3. Characteristic fraction of author production measured for different intervals. The fractions R/Wt and R/Ws represent the prevalence and representativeness of regional author production respectively. R= Number of valid species described by regional authors within the target time interval; Wt= Total number of valid species described within the target time interval: Ws= Total number of valid species described solely by regional authors. Dashed line corresponds to coefficient ς and its maximum corresponds to the period [1999, 2012]. In this period: (i) the overall production is dominated by South American authors, and (ii) the bulk of South American production is included.
FIGURE 1 in Co-authorship networks (and other contextual factors) behind the growth of taxonomy of South American Ephemeroptera: A scientometric approach
FIGURE 1. Number of valid species described by period. Species described by foreign (F), regional (R) and mixed (M) authors are represented by different tones. Note that binned time intervals do not represent equal periods.
Carcea et al., 2021 single-unit recordings during co-housing
<p>These are raw data from single-unit recordings during co-housing experiments, in female mouse (virgin) PVN. These recordings are associated with the Carcea et al., 2021 manuscript. </p>
Data from: Alteration of (frequency-dependent) fitness in time-shift experiments reveals cryptic co-evolution and uncoordinated stasis in a virtual Jurassic Park
Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent experimental platform for addressing topics in both short-term and long-term evolution, such as whether co-evolving multispecies communities are dominated more by biotic or abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths (Strong and Weak), along with unperturbed Control experiments. We performed several kinds of competition experiments using simplified versions of these communities to see whether long-term stability that was implied previously by ecological and phylogenetic metrics was also reflected in terms of performance, i.e. whether fitness was static over long periods of time. Results from Control and Weak treatment communities revealed almost completely transitive evolution, while Strong treatment communities showed higher incidences of intransitivity, with pre-treatment ecotypes often able to displace some of their post-recovery successors. However, pre-treatment carryovers more often had lower fitness in mixed communities than in their own fully native conditions. Replacement and invasion experiments pitting single ecotypes against pre-treatment reference communities showed that many of the invading ecotypes could measurably alter the fitnesses of one or more residents, usually with depressive effects, and that the strength of these effects increased over time even in the most stable communities. However, invaders taken from Strong treatment communities often had little to no effect on resident performance. While we detected periods of time when the fitness of a particular evolving ecotype remained static, this stasis was not permanent and was uncoordinated, never affecting an entire community at once. Our results lend support to the fitness-deterioration interpretation of the Red Queen hypothesis, and highlight community context-dependence in determining fitness, the shaping of communities by both biotic factors and abiotic forcing, and the illusory nature of evolutionary stasis. Our results also demonstrate the potential of digital evolution studies to illuminate many aspects of evolution in interacting multispecies communities.
Co-occurrence of beaked whale strandings and naval sonar in the Mariana Islands, Western Pacific
<p>Mid-frequency active sonar (MFAS), used for antisubmarine warfare (ASW), has been associated with multiple beaked whale (BW) mass stranding events. Multinational naval ASW exercises have utilized MFAS offshore of the Mariana Archipelago semi-annually since 2006. We report BW and MFAS acoustic activity near the islands of Saipan and Tinian from March 2010 through November 2014. Signals from Cuvier's (<i>Ziphius cavirostris)</i> and Blainville's beaked whales (<i>Mesoplodon densirostris</i>), and a third unidentified BW species were detected throughout the recording period. Both recorders documented MFAS on 21 August 2011 before two Cuvier's beaked whales stranded on 22-23 August 2011. We compared the history of known naval operations and BW strandings from the Mariana Archipelago to consider potential threats to BW populations. Eight BW stranding events between June 2006 and January 2019 each included 1-3 animals. Half of these strandings occurred during, or within 6 days after naval activities, and this co-occurrence is highly significant. We highlight strandings of individual BWs can be associated with ASW, and emphasize the value of ongoing passive acoustic monitoring, especially for beaked whales that are difficult to visually detect at sea. We strongly recommend more visual monitoring efforts, at sea and along coastlines, for stranded cetaceans before, during, and after naval exercises.</p>
Is phylogeographic congruence predicted by historical habitat stability, or ecological co-associations?
<p>Comparative phylogeographic studies can uniquely distinguish idiosyncratic versus community-wide responses to past environmental change. However, to date, impacts of species interactions have been largely overlooked. Here we used non-genetic data to characterize two competing scenarios about expected levels of congruence among five saproxylic invertebrate species (i.e., a wood-feeding cockroach, termite and beetle; a predatory centipede, and a detritivorous millipede) from the southern Appalachians mountains—a topographically complex unglaciated landscape. Under one scenario, abiotic factors primarily drove species' responses, with predicted congruence based on spatial overlap of climatically stable habitat areas estimated for each species via ecological niche modeling. The other scenario considered biotic factors to be most influential, with proxies for actual or potential direct interactions used to predict congruence. Analyses of mitochondrial and nuclear DNA sequence datasets for each species focused on four axes of comparison: the number and distribution of spatial-genetic clusters, phylogeographic structure, changes in long-term effective population size, and historical gene flow dynamics. Overall, we found stronger support for ecological co-associations scenario, suggesting an important influence of biotic factors in constraining or facilitating species' responses to Pleistocene climatic cycles. However, there was an imperfect fit between this scenario's predictions and outcomes of empirical data analyses. Thus, our conclusions are compelling, but tentative. This work advances comparative phylogeography by expanding the scope of inferences beyond abiotic drivers, and provides insights into the evolutionary history of a functionally important ecological community, within a globally recognized center of endemism.</p>
Eco-friendly fluorimetric approaches for the simultaneous estimation of the co-administered ternary mixture: etoposide, moxifloxacin, and nalbuphine
<p>Antineoplastic drugs as etoposide (ETO) are widely utilized in leukemia cancer. Patient with leukemia cancer has a relative infection with pneumonia treated by fluoroquinolones as moxifloxacin HCL (MOX). Because opioid analgesic as nalbuphine HCL (NAL) does not have a ceiling dose, it is used to manage the distasteful sensory in leukemia cancer. Green chemistry advances innovative design to keep a healthy environment. Consequently, innovatory green processes for synchronous spectrofluorimetric quantification of a ternary mixture of antineoplastic, fluoroquinolone, and opioid analgesic drugs. The present study provides two eco-friendly synchronous fluorimetric processes (conventional and first derivative), conventional for MOX and the first derivative for ETO and NAL quantification. Conventional synchronous fluorimetric of MOX was monitored at 371 nm, while the first derivative synchronous fluorimetric of ETO and NAL was measured at 257 and 273 nm, respectively, in ethanol. The synchronous fluorescence was scanned at λ of 60 nm for both processes. Environmentally friendly solvent as ethanol has a major role in the sensitivity, reproducibility, and quantitation of innovative processes. The outcomes of these designed environmentally friendly processes, a linear correlation was described in the ranges of 0.04-0.40, 0.1-1.0, and 0.5-5.0 g/mL for MOX, ETO, and NAL, respectively. Accordingly, several pharmaceutical dosages were achieved within the range simply and precisely. Additionally, synchronous assessment of ETO, MOX, and NAL in the biological fluid was attained by facile protein precipitation technique. These innovatory green processes were evaluated as accurate and precise processes regarding ICH roles. Greener innovative synchronous fluorimetric processes were corroborated by applying the National Environmental Methods Index, Analytical Eco-scale, and Green Analytical Procedure Index, which provides a novelty of the current study.</p>
Figure 8 in ZIP code matters: Nicsmirnovius paggii, a new species from fitzpatriki-complex (Cladocera: Chydoridae) does not co-occur with Nicsmirnovius incredibilis
Figure 8. Approximated geographical range of Nicsmirnovius paggii sp. nov. (a) and Nicsmirnovius incredibilis (b). According to data, Nicsmirnovius paggii sp. nov. does not occur in the medium and lower portions of the Amazonas River Basin. We can consider that Nicsmirnovius incredibilis is an exclusive species of medium and lower portions of the Amazonas River Basin.
Figure 5 in ZIP code matters: Nicsmirnovius paggii, a new species from fitzpatriki-complex (Cladocera: Chydoridae) does not co-occur with Nicsmirnovius incredibilis
Figure 5. Nicsmirnovius paggii sp. nov. from São Bartolomeu River, Paraná River Basin, Brazil. (a) First limb; (b) idem – endite 3, element; (c) idem – ODL and IDL; (d) Second limb, arrows indicate elements; (e) Third limb, exopodite; (f) idem – distal endite; (g) idem – basal endite; (h) Fourth limb, exopodite; (i) idem – variation on the seta 5; (j) idem – endites, arrow indicate elements; (k) Fifth limb, arrow indicate elements; (l) idem – variation on the seta 2 of inner lobe. Scale bar = 50 μm.
Figure 4 in ZIP code matters: Nicsmirnovius paggii, a new species from fitzpatriki-complex (Cladocera: Chydoridae) does not co-occur with Nicsmirnovius incredibilis
Figure 4. Nicsmirnovius paggii sp. nov. from São Bartolomeu River, Paraná River Basin, Brazil. (a) Habitus of parthenogenetic female; (b) Dorsal view of carapace; (c) Ventral view of carapace; (d) Ventral margin of carapace; (e) Posteroventral corner of carapace; (f) Head shield; (g) Head pores; (h) Labrum; (i) Maxilla; (j, k) Antennules; (l) Antenna. Scale bars = 50 μm in (e, g–l); 100 μm in (a–d, f).
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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.