Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Antimicrobial peptides emerge as compounds that can alleviate the global health hazard of antimicrobial resistance, prompting a need for novel computational approaches to peptide generation. Here, we propose HydrAMP, a conditional variational autoencoder that learns lower-dimensional, continuous representation of peptides and captures their antimic...
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Full title
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
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TN_cdi_doaj_primary_oai_doaj_org_article_5c436eeedaa54f1aaf4e657e6e0f9a55
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_5c436eeedaa54f1aaf4e657e6e0f9a55
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ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-023-36994-z
