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/10.1093/bioinformatics/btaa917
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/btaa917amPEPpy is implemented in Python 3 and freely available through GitHub: https://github.com/tlawrence3/amPEPpy
