Researchers from Pacific Northwest National Laboratory created and embedded a physics-informed deep neural network that can learn as it processes data.
Scientists can now generate a protein database directly from proteomics data gathered from a specific soil sample using a digital tool and deep learning computer model called Kaiko.
IDREAM research shows that keeping only the most important two- and three-body terms in reactive force fields can decrease computational cost by one order of magnitude, while preserving satisfactory accuracy.
This study profiled the 24-hour rhythmicity in bile salt hydrolase enzyme activity using simple fluorescence assay and the results showed that this rhythmicity is influenced by feeding patterns of the host.
Highly precise and controllable single-atom catalysts are affected by reaction conditions, which can alter the bonding around the atoms and the activity.
Across the United States, organic carbon concentration imposes a primary control on river sediment respiration, with additional influences from organic matter chemistry.
New research from PNNL and Washington State University collaborators connects the microbiome in the gut to circadian rhythms, suggesting a role for the microbiome as an internal regulator.
The popular approach of organizing soil bacteria into fast- or slow-growing groups is problematic because most bacteria grow at comparable rates in soil.
Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.
A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.
SAGE is a high-efficiency genome integration strategy for bacteria that makes the stable introduction of new traits simple for newly discovered microbes.
