Multiclass classification performance of MHC class I binding epitope prediction tools: (a) VUS; (b) SPE; (c) SRCC; (d): R-squared of linear regression. IC50 thresholds of 50 nM and 500 nM were used to classifying experimental measurements between strong binder, weak binder, and non-binder. The box plots of VUS and SRCC show values covering 95% confidence level. Note that IC50 is not calculated in MixMHCpred.</p
<p>Number of predicted T-cell epitopes from the 38-mer C-terminal fragment of α-Syn are in brackets....
MHC-peptide binding prediction has been widely used for understanding the immune response of individ...
BACKGROUND: It is important to accurately determine the performance of peptide:MHC binding predictio...
Multiclass classification performance of MHC-II binding epitope prediction tools: (a) VUS; (b) SPE; ...
Reliability of predicting absolute affinities of strong binding MHC Class I and II epitopes for (a) ...
(a) Box plots showing the quartile distribution of binding affinity rankings as predicted by NetMHC4...
A number of machine learning-based predictors have been developed for identifying immunogenic T-cell...
BACKGROUND: Experimental screening of large sets of peptides with respect to their MHC binding capab...
Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility comple...
Background: Protein antigens and their specific epitopes are formulation targets for epitope-based v...
<b>Background</b> Protein antigens and their specific epitopes are formulation target...
BACKGROUND: Protein antigens and their specific epitopes are formulation targets for epitope-based v...
Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility comple...
<p>For each MHC allele, the number of predicted epitopes within a given synthetic peptide is shown o...
Motivation: Computational methods for the prediction of peptide-MHC binding have become an integral ...
<p>Number of predicted T-cell epitopes from the 38-mer C-terminal fragment of α-Syn are in brackets....
MHC-peptide binding prediction has been widely used for understanding the immune response of individ...
BACKGROUND: It is important to accurately determine the performance of peptide:MHC binding predictio...
Multiclass classification performance of MHC-II binding epitope prediction tools: (a) VUS; (b) SPE; ...
Reliability of predicting absolute affinities of strong binding MHC Class I and II epitopes for (a) ...
(a) Box plots showing the quartile distribution of binding affinity rankings as predicted by NetMHC4...
A number of machine learning-based predictors have been developed for identifying immunogenic T-cell...
BACKGROUND: Experimental screening of large sets of peptides with respect to their MHC binding capab...
Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility comple...
Background: Protein antigens and their specific epitopes are formulation targets for epitope-based v...
<b>Background</b> Protein antigens and their specific epitopes are formulation target...
BACKGROUND: Protein antigens and their specific epitopes are formulation targets for epitope-based v...
Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility comple...
<p>For each MHC allele, the number of predicted epitopes within a given synthetic peptide is shown o...
Motivation: Computational methods for the prediction of peptide-MHC binding have become an integral ...
<p>Number of predicted T-cell epitopes from the 38-mer C-terminal fragment of α-Syn are in brackets....
MHC-peptide binding prediction has been widely used for understanding the immune response of individ...
BACKGROUND: It is important to accurately determine the performance of peptide:MHC binding predictio...