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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
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Epitopemap: a web application for integrated whole proteome epitope prediction
Damien Farrell1, Stephen V Gordon2
1School of Veterinary Medicine, University College Dublin, Belfield, Dublin, Ireland. farrell.damien@gmail.com.
BMC Bioinformatics
|July 15, 2015
Summary
This study introduces Epitopemap, a web tool for T cell epitope prediction. It integrates multiple prediction methods for genome-wide analysis, aiding in the computational screening of pathogens.
Area of Science:
- Immunoinformatics
- Computational Biology
- Genomics
Background:
- MHC binding affinity predictions are crucial for T cell epitope discovery.
- Existing methods lack integrated analysis and genome-wide capabilities.
- A unified approach is needed for efficient epitope prediction.
Purpose of the Study:
- To develop a user-friendly web application for integrating multiple epitope prediction tools.
- To enable simultaneous analysis of T cell epitope predictions across entire proteomes.
- To facilitate computational screening of viral and bacterial genomes.
Main Methods:
- Developed a web application serving as a front-end for diverse, freely available epitope prediction methods.
- Integrated visualization of results from multiple predictors within protein structures.
- Enabled genome-wide analysis and calculation of epitope conservation.
Main Results:
- A novel web application, Epitopemap, was created for calculating and viewing epitope predictions.
- The tool integrates multiple prediction methods for comprehensive analysis.
- Features include single-plot visualization, genome-wide analysis, and epitope conservation estimates.
Conclusions:
- Epitopemap provides a self-contained solution for epitope prediction.
- The application simplifies the computational screening of pathogens.
- It enhances the efficiency of identifying potential T cell epitopes.
