@inbook{e44127bfe23e4ae9af3f4702f0d092e1,
title = "Bioinformatics Tools for the Prediction of T-Cell Epitopes",
abstract = "T-cell responses are activated by specific peptides, called epitopes, presented on the cell surface by MHC molecules. Binding of peptides to the MHC is the most selective step in T-cell antigen presentation and therefore an essential factor in the selection of potential epitopes. Several in-vitro methods have been developed for the determination of peptide binding to MHC molecules, but these are all costly and time-consuming. In consequence, significant effort has been dedicated to the development of in-silico methods to model this event. Here, we describe two such tools, NetMHCcons and NetMHCIIpan, for the prediction of peptide binding to MHC class I and class II molecules, respectively, involved in the activation pathways of CD8+ and CD4+ T cells.",
keywords = "Artificial neural networks, MHC binding, Prediction server, T-cell epitopes",
author = "Massimo Andreatta and Morten Nielsen",
year = "2018",
doi = "10.1007/978-1-4939-7841-0_18",
language = "English",
volume = "1785",
series = "Methods in Molecular Biology",
publisher = "Springer",
pages = "269--281",
editor = "Walker, {John M.}",
booktitle = "Methods in Molecular Biology",
}