The Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) database was generated to mechanistically understand how feedbacks across scales, from molecular to plant to plant populations and communities to ecosystems, govern the resilience of system functions to elevated CO2...

The EyeSea underwater video dataset was assembled for developing algorithms for detecting fish in real world underwater video data. The data were recorded as part of environmental monitoring efforts at three different water power sites.

The long-term goals of this scientific focus area (SFA) are to develop flexible and extensible modeling capabilities that capture the dynamic multiscale interactions among climate, energy, water, land, socioeconomics, critical infrastructure, and other sectors and to use these capabilities to study...

Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson PerCon SFA Project Publication Experimental Data Catalog The Persistence Control of Engineered Functions in Complex Soil Microbiomes Project (PerCon SFA) at Pacific Northwest National Laboratory ( PNNL ) is a Genomic Sciences Program...

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...

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...

OSU-PNNL Superfund Research Program Center is part of the Superfund Research Program (SRP) at Oregon State University, directed by Dr. Robyn Tanguay, bringing together a multidisciplinary team of experts with extensive experience in polycyclic aromatic hydrocarbons (PAHs) research. Using state-of...

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...

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...

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...

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...

Some of the most rapid environmental changes on the planet are experienced in high-latitude regions. These changes affect all Earth system components, including the ocean, atmosphere, cryosphere, and marine and terrestrial ecosystems, and have both regional and global implications. The main...

Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Interferon-Stimulated Response to Virus Infection Background The human host Interferon ( IFN ) alpha, beta, and gamma participate in the body's natural immune response to lethal virus infection and disease. The...

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...

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...