Researchers from PNNL have helped colleagues at OHSU identify lipid molecules required for Zika infection in human cells. The specific lipids involved could also be a clue to why the virus primarily infects brain tissue.

A technology that can quickly detect explosive vapors, deadly chemicals and illicit drugs with unparalleled accuracy has been named the 2020 Innovation of the Year by GeekWire, the Seattle-based technology news company.

Researchers from 25 institutions around the country, including PNNL, are working to find out how exercise changes the molecular makeup of our cells to generate health benefits.

After 50 years in science and on the eve of retirement, Laboratory Fellow Karin Rodland, a cancer cell biologist at PNNL, is working on experiments she has dreamed about for decades.

Accurate identification of metabolites, and other small chemicals, in biological and environmental samples has historically fallen short when using traditional methods.

A new study using proteogenomics to compare cancerous tissue with normal fallopian tube samples advances insights about the molecular machinery that underlies ovarian cancer.

Artificial intelligence helps researchers identify metabolites, the small molecules that underlie life.

PNNL scientists are on the front lines fighting against biological threats through early detection, diagnosis, and prevention strategies.

A new study focusing on the proteins involved in endometrial cancer, commonly known as uterine cancer, offers insights about which patients will need aggressive treatment and which won’t.

PNNL scientists Richard (Dick) Smith and Ljiljana (Lili) Paša-Tolić are recognized by The Analytical Scientist in its 2019 Power List as two of 2019’s top 100 minds in analytical science.

Vapor detection technology developed at PNNL can quickly and accurately identify explosives, deadly chemicals, and illicit drugs.

Jaehun Chun spoke at a National Academies of Sciences, Engineering, and Medicine open data-gathering session on separation science.

Fifteen PNNL scientists are part of a team that has identified a set of biomarkers that indicate which patients infected with the Ebola virus are most at risk of dying from the disease.

The Multi-omics for Microbiomes conference focused on different approaches that let researchers paint better pictures of microbial communities.