Understanding molecular modifications of proteins in the red yeast could help scientists re-engineer the organism’s phenotype.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.

PNNL scientists use proteomics to unveil how high-density lipoproteins protect against cholesterol accumulation in the artery wall.

Computing and artificial intelligence aid scientists who seek to understand function-driven design and control of biological systems.

New apps help researchers with statistical analyses of data.

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.

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

A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.

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.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.