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Please cite as : Zegeye E., C.J. Brislawn, Y. Farris, S.J. Fansler, K.S. Hofmockel, J.K. Jansson, and A.T. Wright, et al. 2019. WA-IsoC_NAG.1.0 (Amplicon 16S/ITS, WA). [Data Set] PNNL DataHub. https://dx.doi.org/10.25584/data.2019-02.700/1506698 Investigation of the successional dynamics of a soil...

Last updated on 2023-05-02T18:08:23+00:00 by LN Anderson Fungal Monoisolate Multi-Omics Data Package DOI "KS4A-Omics1.0_FspDS68" Molecular mechanisms underlying fungal mineral weathering and nutrient translocation in low nutrient environments remain poorly resolved, due to the lack of a platform for...

Rapid remodeling of the soil lipidome in response to a drying-rewetting event - Multi-Omics Data Package DOI Data package contents reported here are the first version and contain pre- and post-processed data acquisition and subsequent downstream analysis files using various data source instrument...

Please cite as : Anderson L.N., J.E. McDermott, and R.S. McClure. 2020. WA-IsoC_MSC1.1.0 (Amplicon 16S rRNA, WA). [Data Set] PNNL DataHub. https://doi.org/10.25584/WAIsoCMSC1/1635272 The soil microbiome is central to the cycling of carbon and other nutrients and to the promotion of plant growth...

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was...

Comprised of 6,426 sample runs, The Environmental Determinants of Diabetes in the Young (TEDDY) proteomics validation study constitutes one of the largest targeted proteomics studies in the literature to date. Making quality control (QC) and donor sample data available to researchers aligns with...