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

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.