Soil microorganisms play fundamental roles in cycling of soil carbon, nitrogen, and other nutrients, yet we have a poor understanding of how soil microbiomes are shaped by their nutritional and physical environment. In this study, we investigated the successional dynamics of a soil microbiome during...
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The novel fungal strain, Fusarium sp. DS 682, was isolated from the rhizosphere of the perennial grass, Bouteloua gracilis , at the Konza Prairie Biological Station in Kansas. This fungal strain is common across North American grasslands and is resilient to environmental fluctuations. The draft...
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MERS-CoV Experiment MDC001 Processed Omics Data Unavailable This experiment evaluated primary human dendritic cells infected with a wild type MERS-CoV (icMERS) virus. Related Experimental Data BioProject: PRJNA315103 GEO: GSE79172 (mRNA transcriptome response) Acknowledgment of Federal Funding The...
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As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program, we are investigating the impact of environmental change on microbial community function in grassland soils. Three grassland soils, representing different moisture regimes, were selected for ultra-deep...
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The soil microbiome is central to the cycling of carbon and other nutrients and to the promotion of plant growth. Despite its importance, analysis of the soil microbiome is difficult due to its sheer complexity, with thousands of interacting species. Here, we reduced this complexity by developing...
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A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery...
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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Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host...
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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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Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection Background The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host...
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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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Person
PerCon SFA, Co-Investigator Vivian Lin earned her PhD in organic chemistry from the University of California, Berkeley with Professor Chris Chang, developing fluorescent probes for imaging redox active small molecules. Afterward, she traveled to Switzerland for a postdoctoral fellowship in the...
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Dataset
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. IA-TmG.1.0 (Metagenome, IA). [Data Set] PNNL DataHub. https://doi.org/10.25584/IATmG1/1635005 To enable a comprehensive survey of the metabolic potential of complex soil...
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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. KS-TmG.1.0 (Metagenome, KS). [Data Set] PNNL DataHub. https://doi.org/10.25584/KSTmG1/1635004 To enable a comprehensive survey of the metabolic potential of complex soil...
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