Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.

Ljiljana Paša-Tolić, a PNNL fellow, is the recipient of the 2024 International Mass Spectrometry Foundation’s Jochen Franzen Award. 

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

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

Joshua Adkins and Jamie Lo will lead PMedIC, Pacific Northwest National Laboratory and Oregon Health & Science University’s joint research institute.

Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.

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.

PNNL chemist Ying Zhu was honored as one of the top 40 researchers under the age of 40 in analytical science by The Analytical Scientist.

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

The Washington State Academy of Sciences consists of more than 300 elected members who are nationally recognized for their scientific and technical expertise.

Kristin Burnum-Johnson presented at two virtual events in June on proteome mapping.

PNNL is lending analytics expertise to a new first-of-its-kind electric-vehicle carsharing program being launched in Hood River, Oregon.

A webapp developed by PNNL in collaboration with the University of Washington to help drive efficiencies for urban delivery drivers is now in the prototype stage and ready for testing.

Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

Researchers at PNNL are contributing artificial intelligence, machine learning, and app development expertise to a U of W project that will ease challenges with urban freight delivery. The project will provide delivery drivers with a tool