Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.

A detailed snapshot of proteins by PNNL scientists marks a big step toward a diagnostic blood test for a deadly form of liver disease.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

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.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

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.

Lauren Charles joins the CABI One Health Editorial Board as an associate editor.

SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy.

New research makes molecular-level calculations of water faster and easier.

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

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

Business, industry, and government careers were a focus of the PNNL-led Mathematics Research Communities conference.

The Washington State Academy of Sciences added six people from PNNL to its 2022 class of inductees.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.