Machine Learning at the Interface of Polymer Science and Biology: How Far Can We Go?
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DOI: 10.1021/acs.biomac.1c01436
Abstract: This Perspective outlines recent progress and future directions for using machine learning (ML), a data-driven method, to address critical questions in the design, synthesis, processing, and characterization of biomacromolecules. The achievement of these tasks requires… read more here.
Keywords: machine learning; polymer science; interface polymer; science biology ... See more keywords