@inproceedings{77023cbfbdb44ed88ae14b94a1e791e4,
title = "Deep Learning Models for Vaccinology: Predicting T-cell Epitopes in C57BL/6 Mice",
abstract = "The C57 Black 6 (C57BL/6) mice are one the earliest and most widely used inbred laboratory animals in biomedical research and vaccine development. We propose developing a bioinformatics system for the identification of T-cell epitopes in C57BL/6 mice by integrating multiple contributing factors critical to the antigen processing and recognition pathway. The interaction between peptides and MHC molecules is a highly specific step in the antigen processing pathway and T-cell mediated immunity. As the first step of the project, we built a computational tool for predicting MHC class I binding peptides for the C57BL/6 mice. Utilizing deep learning methods, we trained and rigorously validated the prediction models using naturally eluted MHC ligands. The prediction models are of high accuracy.",
keywords = "Bioinformatics System, C57BL/6 Mice, Deep Learning, MHC Binding, Prediction Tool, T-cell Epitope",
author = "Zitian Zhen and Yuhe Wang and Keskin, {Derin B.} and Vladimir Brusic and Lou Chitkushev and Zhang, {Guang Lan}",
note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2023.; 19th EAI International Conference on Computer Science and Education in Computer Science, CSECS 2023 ; Conference date: 28-06-2023 Through 29-06-2023",
year = "2023",
doi = "10.1007/978-3-031-44668-9_14",
language = "English",
isbn = "9783031446672",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "182--192",
editor = "Tanya Zlateva and Georgi Tuparov",
booktitle = "Computer Science and Education in Computer Science - 19th EAI International Conference, CSECS 2023, Proceedings",
address = "Germany",
}
