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.

Launching a premier partnership, PNNL and the University of Texas El Paso (UTEP) signed a memorandum of agreement on UTEP’s campus on October 6.

The IAC will advise the Secretary of Commerce on the science and technology needs of the microelectronics industry.

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.

Amelia Hough-Ross, an IT engineer in Research Computing at PNNL, will be presenting at the Wonder Women Tech Ignite Virtual Summit on May 4-5, 2022.

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

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.

PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.

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.