While it’s one small step forward for mouse research, it’s a big step forward for understanding proteins, the molecular workhorses in biological organisms.
Retired PNNL scientist Doug Elliott has received the 2019 Don Klass Award for Excellence in Thermochemical Conversion Science from the Gas Technology Institute.
Jason McDermott is a PNNL computational biologist whose research interests include machine learning, data integration, and network inference. He unravels complex data related to cancer, infectious disease, and soil microbiomes.
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.
In the third year of the DISCOVR Consortium project, the consortium team has identified an algal strain that progressed successfully through multiple evaluation phases.
Researchers from Pacific Northwest National Laboratory reviewed the current state of knowledge about the impacts of climate change on soil microorganisms in different climate-sensitive soil ecosystems.
A new Co-Optima report describes an assessment of 400 biofuel-derived samples and identifies the top ten candidates for blending with petroleum fuel to improve boosted spark ignition engine efficiency.
The microbial communities within the loose, friable aggregations of organic and mineral components in soil are highly organized spatially, shaped in part by the structure of the soil itself.
Nitrogen is a critical nutrient regulating productivity in many ecosystems and influences nutrient availability by affecting organic matter decomposition rates.
Biogeochemical activity in the hyporheic zone (HZ), sediments where the flowing waters of a river mix with shallow groundwater, supports many of the biological processes that occur within a watershed.
Co-authors of a paper in Hydrological Processes led by PNNL researchers Zhangshuan Hou, Timothy Scheibe, and Christopher Murray, produced a map that identifies different classes of sediments which compose the riverbed along the Hanford ...
A multi-institutional team of scientists developed a new sensitivity analysis framework using Bayesian Networks to quantify which parameters and processes in complex multi-physics models are least understood.