New research sheds light on the biomolecular dangers of night shift work.

PNNL contributes to a nationwide research consortium investigating the molecular mechanisms triggered by endurance training.

Scott Baker, the Functional and Systems Biology Group leader at PNNL, has been named to the American Institute for Medical and Biological Engineering's Class of 2024 Fellows.

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.

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

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

PNNL chemist Ying Zhu was honored as one of the top 40 researchers under the age of 40 in analytical science by The Analytical Scientist.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.

The nested nanoPOTS chip is the next generation of technology developed at PNNL to prepare single cells for proteomics.

PNNL researchers contributed to the International Conference on Data Science and Advanced Analytics 2021 Best Paper Award-winning publication.

DOE’s continued support will allow CENATE researchers to advance computing through the evaluation of novel technologies.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.