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.

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.

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.

COVID-19 changed when and where we use electricity. Researchers showed that commonly available total demand data masked the actual changes.

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

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

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.

Reimagining the United States power grid could save consumers $50 billion a year.

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.

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.