ArticleImmunogenetics2008
A probabilistic meta-predictor for the MHC class II binding peptides.
Article in Immunogenetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Design of a multi-epitope vaccine against intestinal parasites associated with colorectal cancer using immunoinformatics approaches.Scientific reports · 2025Article
- Contriving Multi-Epitope Subunit of Vaccine for COVID-19: Immunoinformatics Approaches.Frontiers in immunology · 2020Article
- Peptide binding predictions for HLA DR, DP and DQ molecules.BMC bioinformatics · 2010Article
- Review
- MHC class II epitope predictive algorithms.Immunology · 2010Review
- MetaMHC: a meta approach to predict peptides binding to MHC molecules.Nucleic acids research · 2010Article
- MHC Class II Binding Prediction-A Little Help from a Friend.Journal of biomedicine & biotechnology · 2010Article
- Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods.Bioinformatics (Oxford, England) · 2009Article
- Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research.BMC bioinformatics · 2008Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Several computational methods for the prediction of major histocompatibility complex (MHC) class II binding peptides embodying different strengths and weaknesses have been developed. To provide reliable prediction, it is important to design a system that enables the integration of outcomes from various predictors. The construction of a meta-predictor of this type based on a probabilistic approach is introduced in this paper. The design permits the easy incorporation of results obtained from any number of individual predictors. It is demonstrated that this integrated method outperforms six state-of-the-art individual predictors based on computational studies using MHC class II peptides from 13 HLA alleles and three mouse MHC alleles obtained from the Immune Epitope Database and Analysis Resource. It is concluded that this integrative approach provides a clearly enhanced reliability of prediction. Moreover, this computational framework can be directly extended to MHC class I binding predictions.
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Identifiers
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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.