Machine Learning Makes Magnificent Macromolecules For Medicine
Document Type
Article
Publication Date
8-3-2022
School
Polymer Science and Engineering
Abstract
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.
Publication Title
Matter
Volume
5
Issue
8
First Page
2558
Last Page
2561
Recommended Citation
Cunitz, V.,
Stacy, E.,
Jankoski, P.,
Clemons, T.
(2022). Machine Learning Makes Magnificent Macromolecules For Medicine. Matter, 5(8), 2558-2561.
Available at: https://aquila.usm.edu/fac_pubs/20096