Gok M, Ozcerit AT (2012) Prediction of MHC class I binding peptides with a new feature encoding technique. Cell Immunol 275(1–2):1–4. : 10.1016/j.cellimm.2012.04.005Gok M, Ozcerit AT. Prediction of MHC class I binding peptides with a new feature encoding technique. Cell Immunol...
validated by a series of experiments and achieved state-of-the-art performance in the peptide–MHC–TCR, peptide–MHC and peptide–TCR binding prediction tasks with up to 15% improvements in area under the precision–recall curve taking the peptide–MHC–TCR binding prediction task as an example...
MHCflurry implements class I peptide/MHC binding affinity prediction. The current version provides pan-MHC I predictors supporting any MHC allele of known sequence. MHCflurry runs on Python 3.9+ using thetensorflowneural network library. It exposescommand-lineandPython libraryinterfaces. ...
Here we introduce PUFFIN (Prediction of Uncertainty in MHC-peptide aFFInity using residual networks), a method for predicting MHC-peptide binding that outputs both the “expected affinity” of an input MHC-peptide pair as well as the “uncertainty” of the model about its prediction. PUFFIN has...
Motivated by a text mining model designed for buildinga classifier from labeled and unlabeled examples, we have developed an iterative supervised learningmodel for the prediction of MHC class II binding peptides.Results: A linear programming (LP) model was employed for the learning task at each ...
Deep learning pan‐specific model for interpretable MHC‐I peptide binding prediction with improved attention mechanism. Proteins 89, 866–883 (2021). Article Google Scholar Yang, X., Zhao, L., Wei, F. & Li, J. DeepNetBim: deep learning model for predicting HLA-epitope interactions based ...
(MHC) molecules have an essential role in T-cell activation and initiating an adaptive immune response.Development of methods for prediction of MHC-Peptide binding is important in vaccine design and immunotherapy.In this study,we try to predict the binding between peptides and MHC class II....
It is important to accurately determine the performance of peptide:MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance are cross-validation, in...
Antigen peptides that are presented by a major histocompatibility complex (MHC) and recognized by a T cell receptor (TCR) have an essential role in immunotherapy. Although substantial progress has been made in predicting MHC presentation, accurately pred
Numerous methods have been applied to the problem of predicting MHC binding. Prediction of MHC class I binding has been very successful, reporting prediction accuracies of up to 95% (e.g. [15]). Attempts at predicting class II MHC binding show significantly lower accuracies, although many ...