Large-Scale Structure-Based Prediction of Stable Peptide Binding to Class I HLAs Using Random Forests

Prediction of stable peptide binding to Class I HLAs is an important component for designing immunotherapies. While the best performing predictors are based on machine learning algorithms trained on peptide-HLA (pHLA) sequences, the use of structure for training predictors deserves further explorati...

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Bibliografiske detaljer

Principais autores:	Jayvee R. Abella, Dinler A. Antunes, Cecilia Clementi, Lydia E. Kavraki
Format:	Artigo
Sprog:	Inglês
Udgivet:	Frontiers Media S.A. 2020-07-01
Serier:	Frontiers in Immunology
Fag:	structural modeling random forests machine learning HLA-I peptide binding docking
Online adgang:	https://www.frontiersin.org/article/10.3389/fimmu.2020.01583/full
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