We have developed an iterative supervised learning model for the prediction of MHC class II binding peptides.

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Jan 4, 2024 · We propose RPEMHC, a new deep learning approach based on residue–residue pair encoding to predict the binding affinity between peptides and MHC.

Jun 13, 2023 · A machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4 + ...

A bioinformatic method was developed for the prediction of peptide binding to MHC class II molecules and its application to the identification of potential ...

In this work, we developed a method for prediction of human MHC class II binding peptides of variable lengths based on continuous kernel discrimination method.

Jan 21, 2013 · Temporal motif mining using partial periodic patterns can capture information about the sequences well enough to predict the binding of the peptides.

Jun 27, 2022 · We propose a novel deep learning-based method, DeepMHCII, for accurate MHC-II peptide binding affinity prediction by incorporating biological ...

May 5, 2023 · This paper develops a capsule neural network-based method to efficiently capture the peptide-MHC complex features to predict the peptide-MHC class I binding.

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