Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.
Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.
High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.
This study demonstrated that a large-scale flooding experiment in coastal Maryland, USA, aiming to understand how freshwater and saltwater floods may alter soil biogeochemical cycles and vegetation in a deciduous coastal forest.
Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.
Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.
Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.
ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.