Showing 1 - 15 of 45
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...
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...
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...

"Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules" The soil microbiome represents one of the most complex microbial communities on the planet, encompassing thousands of taxa and metabolic pathways, rendering holistic analyses computationally intensive and difficult. Here...

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...

Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to Ebola Virus Infection Background Ebola virus ( EBOV ) is a high risk biological agent, belonging to the Flaviviridae family, and is classified as a Category A priority pathogen by the National Institute...

  1. Datasets

    6

Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to Influenza A Virus Infection Background Influenza A virus ( IAV ) is a high risk biological agent belonging to the Orthomyxoviridae family is classified as a Category C priority pathogen by the National...

  1. Datasets

    8

Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to MERS-CoV Virus Infection Background Middle East Respiratory Syndrome coronavirus ( MERS-CoV ), part of the Coronaviridae family, is classified as a Category C priority pathogen by the National Institute...

  1. Datasets

    15

Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to West Nile Virus Infection Background West Nile virus ( WNV ) belongs to the mosquito-borne Flaviviridae family and is classified as a Category A priority pathogen by the National Institute of Allergy and...

  1. Datasets

    11

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...

  1. Datasets

    45

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...

  1. 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...

  1. 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...

  1. Datasets

    3

Biography Kristin Burnum-Johnson is a senior scientist and team lead of the Biomolecular Pathways team at PNNL. Burnum-Johnson earned her PhD in Biochemistry from Vanderbilt University with Professor Richard M. Caprioli and then completed a postdoctoral fellowship at PNNL with Dr. Richard D. Smith...