MHC presentation prediction
3 papers with code • 0 benchmarks • 0 datasets
Task solves important immunological problem, which is predicting whether given peptide will present on given MHC.
Benchmarks
These leaderboards are used to track progress in MHC presentation prediction
Most implemented papers
HLA class I binding prediction via convolutional neural networks
We then propose a deep convolutional neural network architecture, name HLA-CNN, for the task of HLA class I-peptide binding prediction.
Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction
ziqi92/peptide-binding-prediction
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T-cell receptors can recognize foreign peptides bound to major histocompatibility complex (MHC) class-I proteins, and thus trigger the adaptive immune response.
Interpreting BERT architecture predictions for peptide presentation by MHC class I proteins
In particular, we find that amino acids close to the peptides' N- and C-terminals are highly relevant.
