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915
datasets available to search
ShareScore release 0.7.1
Dataset results
915 results for “metagenomics”
Data from: Key roles for freshwater Actinobacteria revealed by deep metagenomic sequencing
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Data from: Phylogenetic community ecology of soil biodiversity using mitochondrial metagenomics
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Data from: Metagenomic chromosome conformation capture (meta3C) unveils the diversity of chromosome organization in microorganisms
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Data from: Mining for NRPS and PKS genes revealed a high diversity in the Sphagnum bog metagenome
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Data for: Metagenomics show high spatiotemporal virus diversity and ecological compartmentalisation: virus infections of melon, Cucumis melo, crops and adjacent wild communities
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Data from: Using metagenomics to show the efficacy of forest restoration in the New Jersey Pine Barrens
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Data from: Detection and decay rates of prey and prey symbionts in the gut of a predator through metagenomics
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Data from: Microbial life in a fjord: metagenomic analysis of a microbial mat in Chilean Patagonia
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Time-series drinking water metagenomes: Assemblies & MAGs
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Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics
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Endosymbionts' genomes extracted from tick metagenomes
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NGS amplicon metagenomic 16S seq of soybean rhizosphere under contrasting nutrient-deficient and acidic-stress soils
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Supplementary material 1 from: Schenk J, Geisen S, Kleinboelting N, Traunspurger W (2019) Metabarcoding data allow for reliable biomass estimates in the most abundant animals on earth. Metabarcoding and Metagenomics 3: e46704. https://doi.org/10.3897/mbmg.3.46704
: Data type: species data
Supplementary material 1 from: Schenk J, Geisen S, Kleinboelting N, Traunspurger W (2019) Metabarcoding data allow for reliable biomass estimates in the most abundant animals on earth. Metabarcoding and Metagenomics 3: e46704. https://doi.org/10.3897/mbmg.3.46704
: Data type: species data
Supplementary material 8 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 5 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 4 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 3 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 6 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 7 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
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.