Learning MHC I—peptide binding
… Combining the threading approach with a machine learning philosophy of fitting to data,
we show that it is possible to estimate a pairwise potential matrix and also learn additional …
we show that it is possible to estimate a pairwise potential matrix and also learn additional …
Evaluation of machine learning methods to predict peptide binding to MHC Class I proteins
… to predict peptide-MHC binding, and a number of methods, trained using results of binding
… We evaluated several recent methods to predict peptide-MHC Class I binding affinities and …
… We evaluated several recent methods to predict peptide-MHC Class I binding affinities and …
Novel machine learning methods for MHC class I binding prediction
… We propose to use Multiple Kernel Learning (MKL) [9] to learn the weights βs,k of the
individual components (see Equation 11) along with the respective classifiers. In particular, we …
individual components (see Equation 11) along with the respective classifiers. In particular, we …
A review on the methods of peptide-MHC binding prediction
Y Liu, X Ouyang, ZX Xiao, L Zhang… - Current …, 2020 - ingentaconnect.com
… Some of them employ matrix models or machine learning models based on the sequence
characteristic embedded in peptides or MHC to predict the binding ability of peptides to MHC. …
characteristic embedded in peptides or MHC to predict the binding ability of peptides to MHC. …
Efficient peptide–MHC-I binding prediction for alleles with few known binders
… that is able to learn peptide–MHC-I binding models for many … the MHC–peptide binding
benchmark recently proposed by Peters et al. (2006) who gathered quantitative peptide-binding …
benchmark recently proposed by Peters et al. (2006) who gathered quantitative peptide-binding …
Prediction of peptide binding to MHC using machine learning with sequence and structure-based feature sets
MP Aranha, C Spooner, O Demerdash, B Czejdo… - … et Biophysica Acta (BBA …, 2020 - Elsevier
… Machine learning models trained on sequence data exist for peptide:MHC (p:MHC) binding
… descriptor sets to predict peptide binding to a well-studied model mouse MHC I allele, H-2D …
… descriptor sets to predict peptide binding to a well-studied model mouse MHC I allele, H-2D …
[HTML][HTML] Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes
J Racle, P Guillaume, J Schmidt, J Michaux, A Larabi… - Immunity, 2023 - cell.com
… determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP …
-learning framework to accurately predict binding specificities and ligands of any MHC-II …
-learning framework to accurately predict binding specificities and ligands of any MHC-II …
Immunoinformatics: predicting peptide–MHC binding
… An important shortcoming of the early machine learning prediction methods for MHC class
I peptide binding was that they (as most other early machine learning methods) required the …
I peptide binding was that they (as most other early machine learning methods) required the …
Machine learning reveals a non‐canonical mode of peptide binding to MHC class II molecules
… : they load short peptide fragments derived from extracellular … the peptide binds lying more
or less flat in the MHC groove, … great majority of peptides bind to the MHC using this canonical …
or less flat in the MHC groove, … great majority of peptides bind to the MHC using this canonical …
Prediction of MHC-peptide binding: a systematic and comprehensive overview
EM Lafuente, PA Reche - Current pharmaceutical design, 2009 - ingentaconnect.com
… methods for predicting MHC-peptide binding that improve the … methods for predicting
MHC-peptide binding and discuss … Learning regression models for predicting the binding affinity …
MHC-peptide binding and discuss … Learning regression models for predicting the binding affinity …
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