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130
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Dataset results
130 results for “Human microbiome”
Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease.
<p>Contains all intermediate data files for the article <strong>Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease, </strong>Quinn-Bohmann et al. 2024. </p> <p>NP and OP refers to nasopharyngeal or oropharyngeal samples, respectively. As some study identifiers are duplicated across these groups, qiime_NP and qiime_OP should be unzipped in distinct directories. The same applies for metadata data files. </p> <p>Analyses of these data can be found at https://github.com/Gibbons-Lab/2023_URTmetaanalysis/tree/main. </p>
Data supporting publication "Metagenomic Immunoglobulin Sequencing (MIG-Seq) Exposes Patterns of IgA Antibody Binding in the Healthy Human Gut Microbiome"
<p>Data supporting publication "Metagenomic Immunoglobulin Sequencing (MIG-Seq) Exposes Patterns of IgA Antibody Binding in the Healthy Human Gut Microbiome"</p>
Human Microbiome Action - Social Media Templates
<p>This comprehensive resource pack includes ready-to-use messages in PNG format and versatile templates for Twitter/X, LinkedIn, and Instagram available as PowerPoint files. Designed to streamline your communication efforts, these templates enable you to effectively share the latest advancements and insights in human microbiome research with your audience.</p>
Data for "A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies"
<p>Data for the manuscript: A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies (see also https://doi.org/10.1101/2022.05.09.491139)</p>
Source Data: No evidence for a common blood microbiome based on a population study of 9,770 healthy humans
<p>Source data for manuscript titled: 'No evidence for a common blood microbiome based on a population study of 9,770 healthy humans' (https://www.biorxiv.org/content/10.1101/2022.07.29.502098v1)</p>
Growth and Microbiome Development in Very Low Birth Weight Infants Fed Primarily Mother's Own Milk vs. Donor Human Milk
ClinicalTrials.gov study NCT02573779. IPD Sharing: Not stated. Countries: 1. Publications: 29.
Mechanism of Microbiome-induced Insulin Resistance in Humans (Aim2)
ClinicalTrials.gov study NCT02127125. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Nor climate, nor human impact factors: Chytrid infection shapes the skin microbiome of an endemic amphibian along a biodiversity hotspot
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Proteomic and N-glycomic comparison of synthetic and bovine whey proteins and their effect on human gut microbiomes in vitro
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Bacterial composition of the human milk microbiome across lactation
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Dynamics of bacterial recombination in the human gut microbiome — figure data
<p>Data associated with Figures 1-6, S1-41 in the manuscript "Dynamics of bacterial recombination in the human gut microbiome" (DOI: <a href="https://doi.org/10.1101/2022.08.24.505183">10.1101/2022.08.24.505183)</a></p>
Quantifying live bacteria in the human skin microbiome reveals reduced interpersonal variability
<p>Using flow-cytometry and metagenomics, coupled with an upstream pre-processing step to remove relic-DNA (DNA left behind from dead or dying cells) to determine the live population of the skin microbiome. Repository contains important feature tables, counts tables, sequencing preprocessing scripts and feature table analysis scripts.</p>
Pre-computed MGCs from human microbiome reference genomes
<p>This dataset contains non-redundant metabolic gene clusters (MGCs) collected by running gutSMASH and BiG-MAP on a collection of unique high-quality reference genomes. This collection consist of MGCs predicted by gutSMASH using 1,520 genomes from the Culturable Genome Reference (CGR), 2,308 genomes from the Human Microbiome Project (HMP) and 414 Clostridia genomes as input and then filtered for redundancy using the family module of BiG-MAP. For more information: <a href="http://doi.org/10.1101/2021.02.25.432841">https://doi.org/10.1101/2021.02.25.432841</a></p> <p><strong>BiG-MAP_mg.pickle</strong> -> suitable for <strong>metagenome</strong> analyses</p> <p><strong>BiG-MAP_mt.pickle </strong>-> suitable for <strong>metatranscriptome </strong>analyses</p> <p>The files can be used as direct input in the third module of BiG-MAP (BiG-MAP.map.py: <a href="https://github.com/medema-group/BiG-MAP">https://github.com/medema-group/BiG-MAP</a>).</p>
In silico mock communities for evaluation of taxonomic profilers across eukaryotes in the human microbiome
<p><em>In silico </em>mock communities generated with CAMISIM for benchmarking the performance of taxonomic profilers across prokaryotic (50 communities), eukaryotic (30 communities), and viral communities (10 communities) of the human microbiome. Metagenomes were generated using CAMISIM (Fritz et al., 2019), which simulates 2.1 Gb of Illumina 2 ×150 bp paired end reads with the default HiSeq 2500 error profile and a mean insert size of 200 bp.</p> <p><strong>Eukaryotic communities<br></strong>30 eukaryotic <em>in silico</em> metagenomes comprising up to 200 randomly sampled genomes from a set of 113 eukaryotic species (See Supplementary Table 2 from the paper) corresponding to the eukaryotic species within both CHAMP and MetaPhlAn 4 (Blanco-Míguez et al., 2023) databasess.</p> <p><strong>Prokaryotic and viral communities</strong></p> <p>In silico data for prokaryotic and viral communities from the human microbiome can be found here: <a href="https://doi.org/10.5281/zenodo.10777404">doi: 10.5281/zenodo.10777404</a></p> <p><strong>References</strong></p> <p>Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., et al. (2023). Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. <em>Nature Biotechnology 2023 41:11</em> 41, 1633–1644. doi: 10.1038/s41587-023-01688-w</p> <p>Fritz, A., Hofmann, P., Majda, S., Dahms, E., Dröge, J., Fiedler, J., et al. (2019). CAMISIM: Simulating metagenomes and microbial communities. <em>Microbiome</em> 7, 1–12. doi: 10.1186/S40168-019-0633-6/FIGURES/5</p>
CAMI2 Challenge - Human Microbiome Project Toy Database - sample 19 - regenerated using recent RefSeq representative genomes
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The Human Microbiome in Immune-Mediated Diseases
ClinicalTrials.gov study NCT02394964. IPD Sharing: NO. Countries: 1. Publications: 6.
Human Milk and Infant Intestinal Microbiome Study
ClinicalTrials.gov study NCT03181269. IPD Sharing: NO. Countries: 1. Publications: 11.
Effects of a Novel Food Product Containing Microbiota Accessible Carbohydrates on the Human Microbiome
ClinicalTrials.gov study NCT03058575. IPD Sharing: NO. Countries: 1. Publications: 8.
Factors Influencing the Human Gut Microbiome Profile in Multi-ethnic Groups of the Singapore Community (FAMES)
ClinicalTrials.gov study NCT02893709. IPD Sharing: NO. Countries: 1. Publications: 4.
The Role of Human Milk Oligosaccharides and Microbiomes on Infantile Colic and Atopic Dermatitis in Term Infants
ClinicalTrials.gov study NCT05992493. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
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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.