Identifying antimicrobial peptides in genomes using machine learning

Abstract

Legana Fingerhut used machine learning to improve predictions of antimicrobial peptides (AMPs) from protein sequences. Her associated framework was the first to specifically address the problem of identifying AMPs from whole-genome data. Her work leads to improved workflows for identifying novel AMPs which advances our understanding of the innate immune system

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