Peptide-MHC Binding PredictionMajor Histocompatibility Complex (MHC), Binder Predictiondoi:10.1007/978-1-4419-9863-7_101139Werner DubitzkyOlaf WolkenhauerKwangHyun ChoHiroki YokotaSpringer New York
Structure of a pMHC complex. (A) Front view of the crystal structure 1I4F depicting acartoonrepresentation of the MHC (HLA-A*02:01), and asticksrepresentation of the bound peptide (derived from MAGEA4, in pink). The heavy chain of the MHC receptor (alpha), which contains the binding c...
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...
Finally, we will outline our own contribution to this field: the application of QSAR techniques to the prediction of peptide-MHC binding.doi:10.1007/978-0-387-39241-7_9Channa K HattotuwagamaPingping GuanMatthew DaviesDebra J TaylorDarren R Flower...
(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....
Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules K, Sidney J, Sette A, Aoki-Kinoshita KF, Mamitsuka H: Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules... S Zhu,K Udaka,J Sidney,... - 《Bioinformat...
Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles We introduced previously an on-line resource, RANKPEP that uses position specific scoring matrices (PSSMs) or profiles for the prediction of peptide-MHC cl... PA Reche,JP Glutting,Z Hong,....
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...
Further, the standard deviation for AROC was minimum for Weibull distribution, and may be used to train the artificial neural network for HLAA*0201 MHC ClassI binders and nonbinders prediction. 展开 关键词: Tcell Epitope ANN Probability distribution MHC binder/nonbinder ...