Biosciences News

A team that included Banumathi Sankaran of the Molecular Biophysics and Integrated Bioimaging Division studied a protein called σNS, an important component of some viral factories. Understanding how this protein works will foster development of therapeutic strategies against viruses that use similar proteins to replicate.

Berkeley Lab scientists from the Applied Mathematics and Computational Research (AMCR) and Environmental Genomics and Systems Biology (EGSB) Divisions developed RhizoNet, which harnesses the power of artificial intelligence (AI) to automate the process of root image analysis with exceptional accuracy.

Machine learning has a variety of applications in scientific research, from rapidly analyzing datasets to making predictions. At the Joint BioEnergy Institute (JBEI), researchers are using machine learning to find new proteins that play a role in plant gene expression — providing the scientific community with new avenues to explore in bioenergy crop engineering. 

Biosciences researchers have established a powerful new method that couples advanced infrared imaging techniques with statistical machine learning models to quickly and non-invasively determine with high accuracy whether an animal was exposed to radiation—even at extremely low doses almost three months post exposure.

By studying the structure and function of a cyanobacterial protein, researchers have new insights into how these ocean photosynthesizers cycle carbon in changing conditions.