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Protein antibiotics: mind your language

  • Genome Watch
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From Nature Reviews Microbiology

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This month’s Genome Watch examines how natural language processing and machine learning are being implemented in the hunt for new antimicrobial peptides.

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References

  1. Hamid, M. N. & Friedberg, I. Identifying antimicrobial peptides using word embedding with deep recurrent neural networks. Bioinformatics 35, 2009–2016 (2019).

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  3. Kintses, B. et al. Chemical-genetic profiling reveals limited cross-resistance between antimicrobial peptides with different modes of action. Nat. Commun. 10, 5731 (2019).

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Authors and Affiliations

  1. Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK

    Annapaula Correia & Aaron Weimann

  2. Department of Veterinary Medicine, University of Cambridge, Cambridge, UK

    Annapaula Correia

  3. Department of Zoology, University of Oxford, Oxford, UK

    Annapaula Correia

  4. Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK

    Aaron Weimann

Authors
  1. Annapaula Correia
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  2. Aaron Weimann
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Correspondence to Annapaula Correia or Aaron Weimann.

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Correia, A., Weimann, A. Protein antibiotics: mind your language. Nat Rev Microbiol 19, 7 (2021). https://doi.org/10.1038/s41579-020-00485-5

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  • DOI: https://doi.org/10.1038/s41579-020-00485-5

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