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MetaMHC: a meta approach to predict peptides binding to MHC molecules
- Source :
- Nucleic Acids Research
- Publication Year :
- 2010
- Publisher :
- Oxford University Press, 2010.
-
Abstract
- As antigenic peptides binding to major histocompatibility complex (MHC) molecules is the prerequisite of cellular immune responses, an accurate computational predictor will be of great benefit to biologists and immunologists for understanding the underlying mechanism of immune recognition as well as facilitating the process of epitope mapping and vaccine design. Although various computational approaches have been developed, recent experimental results on benchmark data sets show that the development of improved predictors is needed, especially for MHC Class II peptide binding. To make the most of current methods and achieve a higher predictive performance, we developed a new web server, MetaMHC, to integrate the outputs of leading predictors by several popular ensemble strategies. MetaMHC consists of two components: MetaMHCI and MetaMHCII for MHC Class I peptide and MHC Class II peptide binding predictions, respectively. Experimental results by both cross-validation and using an independent data set show that the ensemble approaches outperform individual predictors, being statistically significant. MetaMHC is freely available at http://www.biokdd.fudan.edu.cn/Service/MetaMHC.html.
- Subjects :
- Genetics
MHC class II
Internet
Binding Sites
biology
Mechanism (biology)
Histocompatibility Antigens Class I
Histocompatibility Antigens Class II
Peptide binding
Computational biology
Articles
Major histocompatibility complex
Mice
User-Computer Interface
Epitope mapping
MHC class I
biology.protein
Animals
Humans
Binding site
Set (psychology)
Peptides
Software
Subjects
Details
- Language :
- English
- ISSN :
- 13624962 and 03051048
- Volume :
- 38
- Database :
- OpenAIRE
- Journal :
- Nucleic Acids Research
- Accession number :
- edsair.doi.dedup.....bb828a55653f4ee47e12e92aee0aae4c