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[HTML][HTML] Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS computational biology, 2018 - journals.plos.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …
被引用次数：149 相关文章
[HTML] nih.gov

[HTML][HTML] Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS Computational Biology, 2018 - ncbi.nlm.nih.gov
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS Computational Biology, 2018 - go.gale.com
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS computational biology, 2018 - pubmed.ncbi.nlm.nih.gov
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …
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[PDF][PDF] Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS Comput Biol, 2018 - pdfs.semanticscholar.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLOS Computational Biology, 2018 - econpapers.repec.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLOS Computational Biology, 2018 - ideas.repec.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

[引用][C] Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS Computational Biology, 2018 - ui.adsabs.harvard.edu
Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally
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Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes.

W Zhao, X Sher - Plos Computational Biology, 2018 - europepmc.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …

Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes

W Zhao, X Sher - PLoS Computational Biology, 2018 - search.proquest.com
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …