Ferguson Helps Group Reach Machine-Learning Discovery & Design of Membrane-Active Peptides for Biomedicine

11/15/2016 Rick Kubetz

There are approximately 1100 known antimicrobial peptides (AMP) with diverse sequences that can permeate microbial membranes. To help discover the “blueprint” for natural AMP sequences, researchers from the University of Illinois at Urbana-Champaign - led by assistant professor of materials science and engineering Andrew Ferguson - and the University of California, Los Angeles, have developed a new machine learning approach to discover and design ⍺-helical membrane active peptides based on their physicochemical properties.

Written by Rick Kubetz


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This story was published November 15, 2016.