Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...
Cross-reactivity00:42

Cross-reactivity

Overview

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Interacting Species Database (ISDB): Comprehensive Resource for Interspecies Interactions at the Molecular Level.

Bioinformatics (Oxford, England)·2026
Same author

Meet NUM-ENRICH: A Collaborative National Effort to Extend and Harmonize Research Infrastructures Within the German Network University Medicine.

Studies in health technology and informatics·2026
Same author

Enabling Privacy-Preserving Federated Learning in Healthcare: The FLAME Architecture and Policy Framework.

Studies in health technology and informatics·2026
Same author

A Maturity Model for the Enforcement of PETs in Federated Settings.

Studies in health technology and informatics·2026
Same author

Autoantibodies Predictive of Atherosclerosis Progression and Statin Response in Juvenile-Onset SLE: A Biomarker Discovery Study.

medRxiv : the preprint server for health sciences·2026
Same author

Clinical outcome of biomarker-guided therapies in adult neuro-oncology patients: An update from the Tübingen molecular tumor board cohort.

Neuro-oncology advances·2026
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 21, 2026

Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells
13:58

Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells

Published on: October 22, 2012

FRED--a framework for T-cell epitope detection.

Magdalena Feldhahn1, Pierre Dönnes, Philipp Thiel

  • 1Division for Simulation of Biological Systems, WSI/ZBIT, University of Tübingen, Sand 14, D-72076 Tübingen, Germany. feldhahn@informatik.uni-tuebingen.de

Bioinformatics (Oxford, England)
|July 7, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces FRED, an open-source immunoinformatics software framework. FRED aids in predicting T-cell epitopes for vaccine design using machine learning and handles antigen data.

More Related Videos

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
08:09

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

Related Experiment Videos

Last Updated: Jun 21, 2026

Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells
13:58

Peptide:MHC Tetramer-based Enrichment of Epitope-specific T cells

Published on: October 22, 2012

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
08:09

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

Area of Science:

  • Immunoinformatics
  • Computational Biology
  • Vaccine Design

Background:

  • Immunoinformatics has advanced significantly, with computational methods crucial for modern vaccine design.
  • Predicting T-cell epitopes using machine learning is a core component of current vaccine development strategies.
  • Integrating and comparing diverse computational methods is essential for large-scale immunoinformatics analyses.

Purpose of the Study:

  • To develop FRED, an extendable, open-source software framework for immunoinformatics.
  • To provide accessible prediction methods for MHC binding and antigen processing.
  • To establish infrastructure for handling antigen sequence data and epitopes.

Main Methods:

  • FRED is implemented in Python using a modular design.
  • The framework supports the integration of external prediction methods.
  • It includes prediction tools for MHC binding and antigen processing.

Main Results:

  • FRED offers easily accessible prediction methods for MHC binding and antigen processing.
  • The framework provides infrastructure for managing antigen sequence data and epitopes.
  • FRED is an extendable and open-source software solution.

Conclusions:

  • FRED facilitates key tasks in immunoinformatics, particularly in vaccine design.
  • Its modularity and open-source nature allow for easy integration and extension.
  • The software supports computational approaches for T-cell epitope prediction and data handling.