Journal
BIOINFORMATICS
Volume 36, Issue 21, Pages 5262-5263Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa653
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Funding
- James Cook University Research Scholarship
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Antimicrobial peptides (AMPs) are the key components of the innate immune system that protect against pathogens, regulate the microbiome and are promising targets for pharmaceutical research. Computational tools based on machine learning have the potential to aid discovery of genes encoding novel AMPs but existing approaches are not designed for genome-wide scans. To facilitate such genome-wide discovery of AMPs we developed a fast and accurate AMP classification framework, ampir. ampir is designed for high throughput, integrates well with existing bioinformatics pipelines, and has much higher classification accuracy than existing methods when applied to whole genome data.
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