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MACHINE LEARNING GUIDED DESIGN OF VIRAL VECTOR LIBRARIES
MACHINE LEARNING GUIDED DESIGN OF VIRAL VECTOR LIBRARIES Researchers at UC Berkeley have developed a machine learning model that can aide in the design of more efficient viral vector libraries. Directed evolution of biomolecules to generate large numbers of randomized variants is an important innovation in biochemistry. This methodology can be applied...
Published: 8/17/2023   |   Inventor(s): David Schaffer, Jennifer Listgarten, Danqing Zhu, David Brookes
Keywords(s): Machine Learning, Recombinant Adenoviral-Associated Virus (rAAV), Vector
Category(s): Technology Classifications > Software