Use DeepImmuno Immunogenicity Prediction

Overview

DeepImmuno is a deep-learning model for accurate immunogenicity prediction of peptide–MHC complexes, achieving state-of-the-art performance across viral and tumor neoantigen datasets. Leveraging a convolutional neural network trained on a beta-binomial scoring framework, it assigns continuous immunogenicity scores that reflect experimental confidence, outperforming traditional classifiers and existing tools like IEDB and DeepHLApan. DeepImmuno-CNN integrates physicochemical-aware amino acid encodings to model TCR–peptide–MHC interactions and systematically identifies the most salient residues for antigen recognition. Designed for broad HLA allele coverage and stable across varied dataset sizes, the model delivers reliable prioritization of immunogenic epitopes for vaccine and immunotherapy development.

Neurosnap Overview

The DeepImmuno Immunogenicity Prediction online webserver allows anybody with a Neurosnap account to run and access DeepImmuno Immunogenicity Prediction, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.