Deep Learning-Drives Insights into Protein-Protein Interactions
Researchers demonstrate a real-world large-scale application of deep neural network models for discovering novel protein-protein interactions.
Researchers demonstrate a real-world large-scale application of deep neural network models for discovering novel protein-protein interactions.
By confining the transport of electrons and ions in a patterned thin film, scientists alter the material's properties for next-generation electronics.
Study reveals that initial state conditions set up particle flow patterns, helping zero in on key properties of matter that mimics the early universe.
Researchers have published the results from the first experiment at the Facility for Rare Isotope Beams, measurement of 5 new half-lives, in Physical Review Letters.
Researchers identify previously uncharacterized aerosols over an agricultural region in Oklahoma.
Researchers combined crystallographic data and computational studies to investigate plutonium-ligand bonding within a hybrid material construct.
Whole-ecosystem warming at SPRUCE exponentially increased available nutrients for plants, but observed responses were not captured by the ELM-SPRUCE model.
Scientists find a new approach to access unusual excited nuclear levels.
Researchers use particle-resolved model simulations to quantify errors in simulations’ simplified optical properties.
The MINERvA experiment in the NuMI beam at Fermilab has made the first accurate image of the proton using neutrinos instead of light as the probe.
Theorists' hydrodynamic flow calculations accurately describe data from collisions of photons with lead nuclei at the ATLAS experiment.
Suppression of a telltale sign of quark-gluon interactions indicates gluon recombination in dense walls of gluons.