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...

PNNL’s Vision Statement for Equity in the Power Grid Drawing from a wealth of interdisciplinary research in grid modernization, PNNL is spearheading an effort to advance equity and energy justice through the role of scientific research with the goal of building an advanced national power grid...

Predictive Phenomics is addressing the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems .

Clinical Proteomic Tumor Analysis Consortium (CPTAC) ovarian cancer proteogenomics project. Characterization of tumors using proteomics and phosphoproteomics to identify signatures of drug resistance and characterize pathways associated with tumor versus normal tissue.

The Integrated Human-Earth System Dynamics (IHESD) scientific focus area is improving the integrated understanding of the drivers, responses, and feedbacks in global earth system evolution, with a focus on energy, water, land, climate, and the economy. The research vision is to deliver scientific...

Coastal landscapes are increasingly exposed to seawater due to sea level rise and extreme weather events. The biogeochemical responses of these vulnerable ecosystems are poorly understood, limiting our ability to predict how their role in global biogeochemical cycles will shift under future...

Actionable climate science entails the provision of local-to-regional scale climate information to support decision-making regarding climate impacts, adaptation and mitigation. Despite advances in theories, observations, climate modeling techniques, and high performance computing, large...

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...

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...

Spruce and Peatlands Responses Under Changing Environments (SPRUCE) site is the 8.1-ha S1 bog, a Picea mariana [black spruce] – Sphagnum spp. ombrotrophic bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Two field research...

The Community Emissions Data System (CEDS) produces emissions anthropogenic aerosol and precursor compounds over the entire industrial era, from 1750 to the present for use in global Earth system models and Earth system research more broadly. Emissions are produced at the country level by fuel and...

The long term goal of this scientific focus area (SFA) is to transform our understanding of climate-relevant processes and provide more robust model representations of the climate system through the integration of new knowledge on cloud and aerosol populations, and their interactions with each other...