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Updated: Oct 18, 2025
Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
Published on: October 15, 2021
CNN-PepPred: an open-source tool to create convolutional NN models for the discovery of patterns in peptide
Valentin Junet1,2, Xavier Daura2,3,4
1Anaxomics Biotech SL, Barcelona 08008, Spain.
Summary:
The ability to unveil binding patterns in peptide sets has important applications in several biomedical areas, including the development of vaccines. We present an open-source tool, CNN-PepPred, that uses convolutional neural networks to discover such patterns, along with its application to peptide-HLA class II binding prediction. The tool can be used locally on different operating systems, with CPUs or GPUs, to train, evaluate, apply and visualize models.
Availability And Implementation:
CNN-PepPred is freely available as a Python tool with a detailed User's Guide at https://github.com/ComputBiol-IBB/CNN-PepPred. The site includes the peptide sets used in this study, extracted from IEDB (www.iedb.org).
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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