| URL: | http://imed.med.ucm.es/epimhc |
| Full name: | EPIMHC |
| Description: | EPIMHC is a relational database of MHC-binding peptides and T cell epitopes that are observed in real proteins. Currently, the database contains 4867 distinct peptide sequences from various sources, including 84 tumor-associated antigens. |
| Year founded: | 2005 |
| Last update: | 2016 |
| Version: | |
| Accessibility: |
Accessible
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| Country/Region: | Spain |
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| University/Institution: | Complutense University of Madrid |
| Address: | Faculty of Medicine, Complutense University of Madrid, Madrid, Spain |
| City: | Madrid |
| Province/State: | |
| Country/Region: | Spain |
| Contact name (PI/Team): | Pedro Reche |
| Contact email (PI/Helpdesk): | parecheg@med.ucm.es |
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Customized predictions of peptide-MHC binding and T-cell epitopes using EPIMHC. [PMID: 25048133]
Peptide binding to major histocompatibility complex (MHC) molecules is the most selective requisite for T-cell recognition. Therefore, prediction of peptide-MHC binding is the main basis for anticipating T-cell epitopes. A very popular and accurate method to predict peptide-MHC binding is based on motif-profiles and here we show how to make them using EPIMHC (http://imed.med.ucm.es/epimhc/). EPIMHC is a database of T-cell epitopes and MHC-binding peptides that unlike any related resource provides a framework for computational vaccinology. In this chapter, we describe how to derive peptide-MHC binding motif-profiles in EPIMHC and use them to predict peptide-MHC binding and T-cell epitopes. Moreover, we show evidence that customization of peptide-MHC binding predictors can lead to enhanced epitope predictions. |
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EPIMHC: a curated database of MHC-binding peptides for customized computational vaccinology. [PMID: 15657103]
SUMMARY: EPIMHC is a relational database of MHC-binding peptides and T cell epitopes that are observed in real proteins. Currently, the database contains 4867 distinct peptide sequences from various sources, including 84 tumor-associated antigens. The EPIMHC database is accessible through a web server that has been designed to facilitate research in computational vaccinology. Importantly, peptides resulting from a query can be selected to derive specific motif-matrices. Subsequently, these motif-matrices can be used in combination with a dynamic algorithm for predicting MHC-binding peptides from user-provided protein queries. |