ArticleNucleic acids research2010
MetaMHC: a meta approach to predict peptides binding to MHC molecules.
Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Benchmarking sequence-based and AlphaFold-based methods for pMHC-II binding core prediction: distinct strengths and consensus approaches.BMC medical genomics · 2026Article
- DeepMHCII: a novel binding core-aware deep interaction model for accurate MHC-II peptide binding affinity prediction.Bioinformatics (Oxford, England) · 2022Article
- MHC2MIL: a novel multiple instance learning based method for MHC-II peptide binding prediction by considering peptide flanking region and residue positions.BMC genomics · 2014Article
- MHC2SKpan: a novel kernel based approach for pan-specific MHC class II peptide binding prediction.BMC genomics · 2013Article
- Mutated and bacteriophage T4 nanoparticle arrayed F1-V immunogens from Yersinia pestis as next generation plague vaccines.PLoS pathogens · 2013Article
- The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection.Journal of immunology (Baltimore, Md. : 1950) · 2012Article
- Virtual interactomics of proteins from biochemical standpoint.Molecular biology international · 2012Article
- Immunodominant T cell determinants of aquaporin-4, the autoantigen associated with neuromyelitis optica.PloS one · 2010Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.