Lawrence, T. J., et al. 2020. Bioinformatics

amPEPpy 1.0:  A portable and accurate antimicrobial peptide prediction tool

Travis J. Lawrence, Dana L. Carper, Margaret K. Spangler, Alyssa A. Carrell, Tomás A. Rush, Stephen J. Minter, David J. Weston, and Jessy L. Labbé
02 November 2020, Bioinformatics, btaa917; https://doi.org/10.1021/acssynbio.9b00524 

Abstract

Antimicrobial peptides (AMPs) are promising alternative antimicrobial agents. Currently, however, portable, user-friendly, and efficient methods for predicting AMP sequences from genome-scale data are not readily available. Here we present amPEPpy, an open-source, multi-threaded command-line application for predicting AMP sequences using a random forest classifier.

Citation

Travis J Lawrence, Dana L Carper, Margaret K Spangler, Alyssa A Carrell, Tomás A Rush, Stephen J Minter, David J Weston, Jessy L Labbé, amPEPpy 1.0: A portable and accurate antimicrobial peptide prediction tool, Bioinformatics, , btaa917, https://doi.org/10.1093/bioinformatics/btaa917

Outside Links

https://doi.org/10.1093/bioinformatics/btaa917
amPEPpy is implemented in Python 3 and freely available through GitHub: https://github.com/tlawrence3/amPEPpy