A paper by PNNL researchers has been chosen as one of 32 NIEHS Papers of the Year—a top 1% honor in the research field.

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

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.

Silicone wristbands could be more convenient option for collecting exposure data.

Scientists at PNNL are working to better prepare authorities, emergency responders, communities and the grid in the face of increasingly extreme hurricanes.

We are pleased to welcome 20 new joint appointees to PNNL.

EGRASS helps prepare and fortify critical structures to protect against the worst consequences of new hurricanes.

Over three days more than 200 federal, state, and tribal partners gathered to evaluate and walk through the Federal Emergency Management Agency (FEMA) Region 10 Cascadia Subduction Zone Earthquake and Tsunami Response Plan.

The Department of Homeland Security Science and Technology Virtual First Responder Capitol Hill Showcase highlighted PNNL work in fentanyl detection standards and database libraries.

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

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

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

The scientist behind the online cartoon RedPen/BlackPen explains how humor can build bridges between scientists and the public.

PNNL scientists are protecting first responders and others by expanding what’s known about fentanyl, the driver of the opioid epidemic.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Scientists have devised a way to engineer yeast to produce sustainable, eco-friendly commodity chemicals using computing power as a guide.

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

Researchers map nearly 9,000 proteins in the human lungs, providing a clearer picture of development.