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915 results for “metagenomics”
Sweden metagenome raw data
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Croatia metagenome raw data
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Metagenomics reveals sex differences in murine fecal microbiota profile induced by chronic alcohol consumption
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Data from: Protein structure determination using metagenome sequence data
Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families and that metagenome sequence data more than triple the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact-based structure matching, and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the Protein Data Bank. This approach provides the representative models for large protein families originally envisioned as the goal of the Protein Structure Initiative at a fraction of the cost.
USF OmicsHub Metagenomics Workshop demo-data
<p>small demo dataset for metagenomics workshop.</p>
Supplementary material 3 from: Macher T-H, Schütz R, Arle J, Beermann AJ, Koschorreck J, Leese F (2021) Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species. Metabarcoding and Metagenomics 5: e66557. https://doi.org/10.3897/mbmg.5.66557
Table S3. Filtered taXon table
Supplementary material 2 from: Macher T-H, Schütz R, Arle J, Beermann AJ, Koschorreck J, Leese F (2021) Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species. Metabarcoding and Metagenomics 5: e66557. https://doi.org/10.3897/mbmg.5.66557
Table S2. Raw taXon table as created with TaxonTableTools
Supplementary material 1 from: Macher T-H, Schütz R, Arle J, Beermann AJ, Koschorreck J, Leese F (2021) Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species. Metabarcoding and Metagenomics 5: e66557. https://doi.org/10.3897/mbmg.5.66557
Table S1. BLAST taxonomy table
Supplementary material 5 from: Macher T-H, Schütz R, Arle J, Beermann AJ, Koschorreck J, Leese F (2021) Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species. Metabarcoding and Metagenomics 5: e66557. https://doi.org/10.3897/mbmg.5.66557
Figure S2
Supplementary material 4 from: Macher T-H, Schütz R, Arle J, Beermann AJ, Koschorreck J, Leese F (2021) Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species. Metabarcoding and Metagenomics 5: e66557. https://doi.org/10.3897/mbmg.5.66557
Figure S1
Supporting data for the manuscript "Generation of lineage-resolved complete metagenome-assembled genomes in complex microbial communities"
<p>Supporting data for the manuscript titled "Generation of lineage-resolved complete metagenome-assembled genomes in complex microbial communities". The archive includes:</p> <ul> <li>metaFlye assmeblies and graphs for HiFi and CLR datasets.</li> <li>HiFi and CLR3 bins/MAGs produced using bin3C / DAS_Tool</li> <li>HiFi MAG taxonomy identifications and completeness info</li> <li>MAGPhase results on HiFi and CLR assmeblies </li> <li>Krona plots with sample composition analysis</li> <li>rRNA/tRNA annotations for the HiFi assembly</li> </ul>
Supplementary material 4 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Table S3
Supplementary material 6 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Figure S1. Pictures were taken with a digital microscope (Keyence VHX-6000, Keyence, Osaka, Japan)
Supplementary material 1 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Protocol 1 – DIY-DS
Supplementary material 3 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Table S2. Raw read table
Supplementary material 2 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Table S1. PCR primers used in this study
Supplementary material 8 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Figure S3
Supplementary material 5 from: {"en": "Buchner D, Haase P, Leese F (2021) Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics. Metabarcoding and Metagenomics 5: e67533. https://doi.org/10.3897/mbmg.5.67533"}
Script 1
Supplementary material 3 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S3
Supplementary material 5 from: Turunen J, Mykrä H, Elbrecht V, Steinke D, Braukmann T, Aroviita J (2021) The power of metabarcoding: Can we improve bioassessment and biodiversity surveys of stream macroinvertebrate communities? Metabarcoding and Metagenomics 5: e68938. https://doi.org/10.3897/mbmg.5.68938
Table S5
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.