Antimicrobial peptides (AMPs) are ancient and evolutionarily conserved molecules widespread in all living organisms that participate in host defence and/or microbial competition. Due to their positive charge, hydrophobicity and amphipathicity, they preferentially disrupt negatively-charged bacterial membranes. AMPs are considered an important alternative to traditional antibiotics, especially in times when the latter are drastically losing their effectiveness. Therefore, efficient computational tools for AMP prediction are essential to identify the best AMP candidates without undertaking expensive experimental studies. AmpGram is our novel tool for predicting AMPs based on the stacked random forests and n-gram analysis, able to successfully predict antimicrobial peptides in proteomes.
AmpGram is available as R function (
shiny GUI (
AmpGram requires the external package, AmpGramModel, which
contains models necessary to perform the prediction. The model
can be installed using
Maintainer: Michal Burdukiewicz <email@example.com>
Burdukiewicz M, Sidorczuk K, Rafacz D, Pietluch F, Chilimoniuk J, Roediger S, Gagat P. (2020) AmpGram: a proteome screening tool for prediction and design of antimicrobial peptides. (submitted)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.