Researchers have developed a new methodology that uses artificial intelligence (AI) tools to identify and count target viruses more efficiently than previous techniques. The new approach can be used in applications such as pharmaceutical biomanufacturing.

The study serves as a proof of principle for identifying small molecules that disrupt fibril formation without affecting droplet function.

A new study finds the proteins responsible for controlling which genes are expressed in a genome do more than simply turn a gene on or off. Essentially, each type of protein that interacts with a gene produces different behaviors – a finding with ramifications for everything from biomedical therapeutics to biological computing.

A new paper in Remote Sensing is an advancement on a previous study that demonstrated a model that uses generative AI to combine satellite data and physics-based simulations to forecast a wildfire’s path, intensity and growth rate.The original system relied on data from VIIRS, a polar-orbiting satellite that detects heat signatures with relatively high spatial resolution (within a few hundred meters) but revisits the same location only twice a day. The result is precise but intermittent information; a sequence of snapshots separated by long intervals in which the fire continues to evolve. Now, the new paper published in the journal Remote Sensing presents an advancement of the model. The goal is to reduce uncertainty about where and when a fire started, crucial information for predicting its spread.