Identifying antimicrobial peptides using word embedding with deep recurrent neural networks.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Jun 1, 2019
Abstract
MOTIVATION: Antibiotic resistance constitutes a major public health crisis, and finding new sources of antimicrobial drugs is crucial to solving it. Bacteriocins, which are bacterially produced antimicrobial peptide products, are candidates for broadening the available choices of antimicrobials. However, the discovery of new bacteriocins by genomic mining is hampered by their sequences' low complexity and high variance, which frustrates sequence similarity-based searches.