Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

Rebecca O’Neil, a research principal in the Energy and Environment Directorate at PNNL, was invited to testify before the House Committee on Energy and Commerce’s Subcommittee on Energy.

Researchers use multiomics to confirm role of lipid synthesis during infection, leading to model of how to restrict virus replication.

Van Cleve guides conversations on national grid modernization strategies, reinforcing PNNL’s role in connecting science, policy, and industry.

McDermott is co-chairing one of only five organized sessions at the annual Pacific Symposium on Biocomputing.

PNNL researchers Daniel Deng and Yehia Ibrahim join the 2025 class of National Academy of Inventors Fellows.

Pioneering autonomous science facility puts a big focus on tiny microbes and AI-driven science.

PNNL researchers are opening up a new front in the fight to stop viral pathogens, protecting people against multiple viruses.

Capturing protein structural changes in host cells exposes vulnerabilities exploited by viruses to hijack cellular machinery.

An award-winning computing method called poly-streaming accelerates the analysis of massive datasets while using limited memory.

PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

Predicting how organisms’ characteristics respond to not only their genes, but also their environments (a nascent field called predictive phenomics), is extraordinarily challenging. Researchers at PNNL are using AI to tackle that challenge.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

Researchers are uncovering the secrets of a fast-acting molecular messaging network that helps determine how the genetic code plays out.

Understanding molecular modifications of proteins in the red yeast could help scientists re-engineer the organism’s phenotype.

Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

PNNL showcased its expertise in AI, machine learning, and related domains at the International Conference on Machine Learning.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.