A large peptidome dataset improves HLA class I epitope prediction across most of the human populatio...
A large peptidome dataset improves HLA class I epitope prediction across most of the human population
About this item
Full title
Author / Creator
Sarkizova, Siranush , Klaeger, Susan , Le, Phuong M. , Li, Letitia W. , Oliveira, Giacomo , Keshishian, Hasmik , Hartigan, Christina R. , Zhang, Wandi , Braun, David A. , Ligon, Keith L. , Bachireddy, Pavan , Zervantonakis, Ioannis K. , Rosenbluth, Jennifer M. , Ouspenskaia, Tamara , Law, Travis , Justesen, Sune , Stevens, Jonathan , Lane, William J. , Eisenhaure, Thomas , Lan Zhang, Guang , Clauser, Karl R. , Hacohen, Nir , Carr, Steven A. , Wu, Catherine J. and Keskin, Derin B.
Publisher
New York: Nature Publishing Group US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Nature Publishing Group US
Subjects
More information
Scope and Contents
Contents
Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides acr...
Alternative Titles
Full title
A large peptidome dataset improves HLA class I epitope prediction across most of the human population
Authors, Artists and Contributors
Author / Creator
Klaeger, Susan
Le, Phuong M.
Li, Letitia W.
Oliveira, Giacomo
Keshishian, Hasmik
Hartigan, Christina R.
Zhang, Wandi
Braun, David A.
Ligon, Keith L.
Bachireddy, Pavan
Zervantonakis, Ioannis K.
Rosenbluth, Jennifer M.
Ouspenskaia, Tamara
Law, Travis
Justesen, Sune
Stevens, Jonathan
Lane, William J.
Eisenhaure, Thomas
Lan Zhang, Guang
Clauser, Karl R.
Hacohen, Nir
Carr, Steven A.
Wu, Catherine J.
Keskin, Derin B.
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7008090
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7008090
Other Identifiers
ISSN
1087-0156,1546-1696
E-ISSN
1546-1696
DOI
10.1038/s41587-019-0322-9
