Samantha Erwin, a PNNL data scientist, was recently appointed to the Society for Industrial and Applied Mathematics Membership Committee.

In soil, microbes produce and consume methane. Using a technique called pool dilution, researchers can separate the rate of methane production and consumption from the net rate.

Program seeks to develop exceptional scientists, engineers, and operations staff who can materially advance DOE missions.

PNNL researchers helped identify a fragment from the SARS-CoV-2 virus that spurs severe illness.

Pacific Northwest may face increase in summer heat-dome-like stationary waves.

Scientists have learned more about how drug resistance develops in patients with acute myeloid leukemia and how the process might be slowed.

PNNL scientists developed a new method to map exactly how a fungus works with leafcutter ants in a complex microbial community to degrade plant material at the molecular level. The team’s insights are important for biofuels development.

PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.

A streamlined informatics workflow that automatically processes complex data and provides the locations of double bonds in lipids.

The new PTM-Psi workflow opens the door for uncovering molecular insights within proteomics datasets.

An initiative from Washington State University and Snohomish County leaders is aiming to make Paine Field a nexus for testing and improving sustainable aviation fuels made from non-petroleum materials.

Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

Scientists at PNNL have published a new article that focuses on understanding the composition, dynamics, and deployment of beneficial soil microbiomes to get the most out of soil.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

More than a dozen PNNL scientists have been named among the world’s most influential researchers on Clarivate’s 2023 Highly Cited Researchers List.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

PNNL scientists took thousands of measurements of firefighters in training to learn more about how the body responds to vigorous exercise.

A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.