Scientists unravel a secret to oil production in plants, opening up the possibility of increasing production for biofuels and other applications.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

New research sheds light on the biomolecular dangers of night shift work.

Vigorous exercise burns fat more in males than in females, but the benefits of exercise are broad for both sexes.

PNNL contributes to a nationwide research consortium investigating the molecular mechanisms triggered by endurance training.

Data reveals mechanisms in our bodies that can help us fight viral pathogenesis.

PNNL scientists have been studying how rivers and streams breathe. Their research focuses on respiration, organic matter, and natural disturbances that affect rivers and streams.

Scientists have learned more about how to protect the insulin-producing cells that die in patients with Type 1 diabetes.

Scientists have learned more about how drug resistance develops in patients with acute myeloid leukemia and how the process might be slowed.

The new PTM-Psi workflow opens the door for uncovering molecular insights within proteomics datasets.

Scientists developed a process (or pipeline) that combined molecular probes—a specific chemical that binds to microbes carrying out a particular function—with a method that isolated these cells from their complex community.

Scientists screen for nanobodies that recognize wild type and mutant functional proteins to develop a framework to disrupt protein interactions that can cause disease.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The virus that causes COVID-19 takes over the body’s fat-processing system and boosts cellular triglycerides as it causes disease.

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

PNNL scientists publish paper and host workshops to share threat-agnostic vision for biodefense.