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Viral communities detected from three large grassland soil metagenomes with historically different precipitation moisture regimes.
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To better understand the effects of solution chemistry on particle aggregation in the complex legacy tank wastes at the Hanford (WA) and Savannah River (SC) sites, we have performed a series of tumbler small- and ultra-small-angle neutron scattering experiments on 20 wt % solid slurries of...
Understanding, controlling, and preventing aggregation of suspended particles is of fundamental importance in a number of scientific and industrial fields. There are several methods for analyzing aggregate morphology and aggregation kinetics, but small-angle scattering (SAS) techniques provide...
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...
The Phenotypic Response of the Soil Microbiome to Environmental Perturbations Project (Soil Microbiome SFA) at Pacific Northwest National Laboratory is a Genomic Sciences Program Science Focus Area (SFA) Project operating under the Environmental Microbiome Science Research Area. The Soil Microbiome...
Datasets
23
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...
Datasets
1
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...
Datasets
1
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...
Datasets
3
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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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Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. Model Soil Consortium 2 (MSC-2) Bacterial Isolate Genomes. [Data Set] PNNL DataHub. https://doi.org/10.25584/PNNLDH/1986536 Model Soil Consortium 2 (MSC-2) Bacterial Isolate Genomes...
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Inclusion levels of alternative splicing (AS) events of five different varieties (i.e. skipped exon (SE), retained intron (RI), alternative 5’ splice site (A5SS), alternative 3’ splice site (A3SS), and mutually exclusive exons (MXE)) were measured in human blood samples from two separate cohorts of...
Last updated on 2023-05-31T16:35:53+00:00 by LN Anderson PerCon SFA: Sequencing of Sorgoleone Promoting Rhizobacteria Isolates Whole genome sequencing (WGS) of sorgoleone utilizing rhizobacteria strains Pseudomonas sorgoleonovorans SO81 , Burkholderia anthina SO82 , and Acinetobacter pittii SO1 , as...