The origin of the electrical signals recorded at the brain’s surface by electrocorticography (ECoG) has long remained a mystery. Kris Bouchard, a staff scientist in the Biological Systems and Engineering (BSE) Division, led a seven-year research effort to understand precisely which neurons are generating the recorded signals.
New Refinement Technique Promises Greater Protein Structure Accuracy
X-ray free-electron lasers (XFELs) came into use in 2010 for protein crystallography, allowing scientists to study fully hydrated specimens at room temperature without radiation damage. Researchers have developed many new experimental and computational techniques to optimize the technology and draw the most accurate picture of proteins from crystals. Now scientists in the Molecular Biophysics and Integrated Bioimaging (MBIB) Division have developed a new program, diffBragg, which can process every pixel collected from an XFEL for a protein structure independently. In a recent IUCrJ paper, the team led by MBIB Senior Scientist Nicholas Sauter proposed a new processing framework for more accurate determination of protein structures.
Using Machine Learning to Estimate COVID-19’s Seasonal Cycle
A cross-disciplinary team of Berkeley Lab scientists with expertise in climate modeling, data analytics, machine learning, and geospatial analytics is launching a project to determine if the novel coronavirus might be seasonal. The team will apply machine-learning methods to a plethora of health and environmental datasets, combined with high-resolution climate models and seasonal forecasts.
NERSC’s Scientific Computing Power Steps into Coronavirus Battle
Biological Systems and Engineering (BSE) Division Director Blake Simmons is involved in facilitating a City of Hope led project that is using supercomputing resources to scrutinize the viral SARS-CoV-2 genome for insights into the COVID-19 disease in the hope of developing antiviral treatments.
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