University of Oregon bioengineer Calin Plesa has developed technology that creates massive, high-quality biological datasets at unprecedented speed and scale, solving a critical bottleneck that has prevented AI from tackling biology's biggest challenges—from studying cancer-associated genes to designing new proteins to accelerating drug development. In research detailed in the latest edition of Science Advances , Plesa used this technology to uncover genetic factors behind antimicrobial resistance, demonstrating how to generate the vast datasets needed to train powerful machine learning systems faster and cheaper than ever before.
Science Advances
Exploring Antibiotic Resistance in Diverse Homologs of the Dihydrofolate Reductase Protein Family through Broad Mutational Scanning
14-Aug-2025