Researchers at PNNL are pursuing new approaches to understand, predict and control the phenome—the collection of biological traits within an organism shaped by its genes and interactions with the environment.
Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.
Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.
This project sought to assure that research activities centered around different sampling and monitoring efforts in northwest Ohio would not disturb any historical cultural resources.
A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.
Alicia Amerson's passion for science communication, expertise in marine mammal research, and experience in wildlife photography provide a robust foundation for her new role with the Clallam County Marine Resources Committee.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
Although climate change may bring increased precipitation to many parts of the United States, some areas may face drier conditions and lower streamflow, resulting in decreased hydropower generation.
Despite the widespread presence of RNA viruses in soils, little is known about the relative contributions and interactions of biological and environmental factors shaping the composition of soil RNA viral communities.
A team of researchers from Pacific Northwest National Laboratory and the Environmental Molecular Sciences Laboratory developed a new and flexible software tool called “Advanced Spectra PCA Toolbox.”
With her broad experience and background, Starr Abdelhadi was selected from many applicants to join the Women in IT Networking at SC (WINS) program for Super Computing 2024 (SC24).