HDF5 file containing 10,000 hydraulic transmissivity inputs and the corresponding hydraulic pressure field outputs for a two-dimensional saturated flow model of the Hanford Site. The inputs are generated by sampling a 1,000-dimensional Kosambi-Karhunen-Loève (KKL) model of the transmissivity field...
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Machine learning is a core technology that is rapidly advancing within type 1 diabetes (T1D) research. Our Human Islet Research Network (HIRN) grant is studying early cellular response initiating β cell stress in T1D through the generation of heterogenous low- and high-throughput molecular...
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The Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...
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The Diabetes Autoimmunity Study in the Young (DAISY) seeks to find environmental factors that can trigger the development of type 1 diabetes (T1D) in children. DAISY follows children with high-risk of developing T1D based on family history or genetic markers. Genes, diets, infections, and...
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Please cite as : Anderson L.N., W.C. Nelson, J.E. McDermott, R. Wu, S.J. Fansler, Y. Farris, and J.K. Jansson, et al. 2020. WA-TmG.1.0 (Metagenome, WA). [Data Set] PNNL DataHub. https://doi.org/10.25584/WATmG1/1635002 To enable a comprehensive survey of the metabolic potential of complex soil...
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Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. Iso-VIG14.1.0 (Metagenome Derived Viral Genomes, WA/IA/KS). [Data Set] PNNL DataHub. https://doi.org/10.25584/IsoVIG14/1770369 Soil samples were collected in triplicate in the Fall of 2017...
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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...
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Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. IA-TmG.2.0 (Metagenome, IA). [Data Set] PNNL DataHub. https://doi.org/10.25584/IATmG2/1770333 Soil samples were collected in triplicate in the fall of 2017 across the three grassland locations...
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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...
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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...
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Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. WA-TmG.2.0 (Metagenome, WA). [Data Set] PNNL DataHub. https://doi.org/10.25584/WATmG2/1770324 Soil samples were collected in triplicate in the fall of 2017 across the three grassland...