Deep Learning Models for Vaccinology: Predicting T-cell Epitopes in C57BL/6 Mice

Zitian Zhen, Yuhe Wang, Derin B. Keskin, Vladimir Brusic, Lou Chitkushev, Guang Lan Zhang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationComputer Science and Education in Computer Science - 19th EAI International Conference, CSECS 2023, Proceedings
EditorsTanya Zlateva, Georgi Tuparov
PublisherSpringer Science and Business Media Deutschland GmbH
Pages182-192
Number of pages11
ISBN (Print)9783031446672
DOIs
Publication statusPublished - 2023
Event19th EAI International Conference on Computer Science and Education in Computer Science, CSECS 2023 - Boston, United States
Duration: 28 Jun 202329 Jun 2023

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume514 LNICST
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X

Conference

Conference19th EAI International Conference on Computer Science and Education in Computer Science, CSECS 2023
Country/TerritoryUnited States
CityBoston
Period28/06/2329/06/23

Keywords

  • Bioinformatics System
  • C57BL/6 Mice
  • Deep Learning
  • MHC Binding
  • Prediction Tool
  • T-cell Epitope

ASJC Scopus subject areas

  • Computer Networks and Communications

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