Machine Learning Makes Magnificent Macromolecules For Medicine
Polymer Science and Engineering
At the University of Minnesota, scientists explore the application of machine learning to screen a multiparametric library of polymers to investigate the relationship between polymer attributes, payload type, and biological outcomes to optimize polymeric vector development for delivery of nucleic acid payloads.
(2022). Machine Learning Makes Magnificent Macromolecules For Medicine. Matter, 5(8), 2558-2561.
Available at: https://aquila.usm.edu/fac_pubs/20096