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Knight campus bioengineer Calin Plesa developed DropSynth, a technology that creates massive, high-quality biological datasets at unprecedented speed and scale. In their new Science Advances publication, they used DropSynth to generate ~1,500 genes, identifying genetic factors driving antimicrobial resistance across microbes. Beyond antimicrobial resistance, this technology could transform research in cancer genes, viral evolution, and protein design. Importantly, DropSynth generates vast biological datasets for training powerful machine learning systems, addressing a critical bottleneck in using AI for drug development and combating disease resistance. Read more: https://lnkd.in/gEv6t8kB