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.

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

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.

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

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

A study of Middle East Respiratory Syndrome has identified a compound that shows potential in easing the symptoms of coronavirus infections.

PNNL has developed seaweed-based inks and materials for 2-D and 3-D printing that can be used for a multitude of applications in the art, medical, STEM, and other fields.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

Hypergraphs can more faithfully identify important genes in complex immune responses.