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, Jessy Labbé
Abstract
SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: amPEPpy is implemented in Python 3 and is freely available through GitHub (https://github.com/tlawrence3/amPEPpy). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Topics & Concepts
Python (programming language)Computer scienceRandom forestClassifier (UML)Open sourceAntimicrobialAntimicrobial peptidesData miningMachine learningArtificial intelligenceComputational biologySoftwareProgramming languageBiologyMicrobiologyAntimicrobial Peptides and ActivitiesMachine Learning in Bioinformaticsvaccines and immunoinformatics approaches