AxPEP_Frontend - AxPEP

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AxPEP is a collection of sequence-based machine learning methods for antimicrobial peptide (AMP) prediction. It accepts amino acid sequences in FASTA format. It can also screen AMPs directly from the DNA genome sequence.

Input sequences in FASTA format (length >= 5)

Input Sequences

Type manually

Upload FASTA sequences (.fasta)

Upload Genome sequences (.fasta, max. file size 50 MB)

Prediction Methods

AmPEP: Random forest model for sequence of any length

Deep-AmPEP30: Convolutional neural network model for short sequence <=30 residues

RF-AmPEP30: Random forest model for short sequence <=30 residues

BERT-AmPEP60: ProtBERT fine-tuned IC50 AMP prediction models for Escherichia coli and Staphylococcus aureus

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Funding:
This project is supported by the Government of Canada’s New Frontiers in Research Fund (NFRF) (NFRFE-2021-00913) (2022.04-2025.03)