CNN-PepPred: An open-source tool to create convolutional NN models for the discovery of patterns in peptide sets. Application to peptide-MHC class II binding prediction.
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ABSTRACT: 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.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Junet V
PROVIDER: S-EPMC8652105 | biostudies-literature |
REPOSITORIES: biostudies-literature
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