What is it about?
A recurrent neural network with LSTM cells was trained on known helical antimicrobial peptides (AMP) to generate new examples that lie close to the known AMP sequences in peptide space.
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Why is it important?
It is the first application of generative recurrent neural networks for the de novo design of peptide sequences. The model is not restricted to antimicrobial peptides but can be applied to any amino acid sequence of interest to design novel but closely related examples for biological testing.
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This page is a summary of: Recurrent Neural Network Model for Constructive Peptide Design, Journal of Chemical Information and Computer Sciences, January 2018, American Chemical Society (ACS),
DOI: 10.1021/acs.jcim.7b00414.
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