Lauren Charles, a chief data scientist at PNNL, showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.
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.
Armed with some of the world’s most advanced instrumentation, researchers at PNNL are working to analyze huge amounts of data and uncover hidden biological connections.
By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
PNNL biodefense experts seek to identify, understand and mitigate the risks of biological pathogens—whether naturally occurring or intentionally created—so steps can be taken to prepare and respond.
Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.
A compilation of soil viral genomes provides a comprehensive description of the soil virosphere, its potential to impact global biogeochemistry, and an open database for future investigations of soil viral ecology.
Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.
