Comparison of prediction power, indicated by (a) AUC, (b) specificity of binders, and (c) specificity of strong binders, of 9mer-based mhcflurry with 9mer-based NetMHCpan4, 43mer-based testing HLA included (mhcflurry_pan) and testing HLA leave-one-out (mhcflurry_pan_LOO) pan-predictor. Each point represents one HLA type.</p
Computational prediction of the peptides presented on MHC class I proteins is an important tool for ...
Multiclass classification performance of MHC class I binding epitope prediction tools: (a) VUS; (b) ...
<p>For each supertype, 9-mer peptide binding predictions were carried out and ratios of probability ...
Motivation: MHC:peptide binding plays a central role in activating the immune surveillance. Computat...
(a) ROC curves of 10-mer predictions with AUC value shown after each method. (b) Boxplots of AUC and...
(a) Box plots showing the quartile distribution of binding affinity rankings as predicted by NetMHC4...
<p>Note: For HLA-A*01∶01, HLA-A*24∶02 and HLA-A*02∶11 percentile score was calculated using ANN and ...
A number of machine learning-based predictors have been developed for identifying immunogenic T-cell...
Identification of T-cell epitopes (parts of antigenic proteins to which the T-cells receptor respond...
<p>A comparison of the measured (black) vs. predicted (dashed) population-based epitope maps in HVTN...
Background: Protein antigens and their specific epitopes are formulation targets for epitope-based v...
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...
<p><b>A</b>: Fraction of the true positives among the top 1% predictions (PP1%) for the naturally pr...
Reliability of predicting absolute affinities of strong binding MHC Class I and II epitopes for (a) ...
Computational prediction of the peptides presented on MHC class I proteins is an important tool for ...
Multiclass classification performance of MHC class I binding epitope prediction tools: (a) VUS; (b) ...
<p>For each supertype, 9-mer peptide binding predictions were carried out and ratios of probability ...
Motivation: MHC:peptide binding plays a central role in activating the immune surveillance. Computat...
(a) ROC curves of 10-mer predictions with AUC value shown after each method. (b) Boxplots of AUC and...
(a) Box plots showing the quartile distribution of binding affinity rankings as predicted by NetMHC4...
<p>Note: For HLA-A*01∶01, HLA-A*24∶02 and HLA-A*02∶11 percentile score was calculated using ANN and ...
A number of machine learning-based predictors have been developed for identifying immunogenic T-cell...
Identification of T-cell epitopes (parts of antigenic proteins to which the T-cells receptor respond...
<p>A comparison of the measured (black) vs. predicted (dashed) population-based epitope maps in HVTN...
Background: Protein antigens and their specific epitopes are formulation targets for epitope-based v...
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...
<p><b>A</b>: Fraction of the true positives among the top 1% predictions (PP1%) for the naturally pr...
Reliability of predicting absolute affinities of strong binding MHC Class I and II epitopes for (a) ...
Computational prediction of the peptides presented on MHC class I proteins is an important tool for ...
Multiclass classification performance of MHC class I binding epitope prediction tools: (a) VUS; (b) ...
<p>For each supertype, 9-mer peptide binding predictions were carried out and ratios of probability ...
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