ArticleBMC bioinformatics2006
EpiJen: a server for multistep T cell epitope prediction.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
85 citing papers in PubMed.
- Systems Vaccinology-Integrated Proteomics to Develop a Novel Prophylactic and Therapeutic Vaccine Against Human Papillomavirus 16.Bioinformatics and biology insights · 2026Article
- Reverse vaccinology-driven construction and bioinformatics validation of a multi-epitope vaccine against Brucella spp.Scientific reports · 2025Article
- Deep learning in next-generation vaccine development for infectious diseases.Molecular therapy. Nucleic acids · 2025Review
- Immunogenicity ofPathogens (Basel, Switzerland) · 2025Article
- In silico design of Ebola virus Glycoprotein antigenic peptides as vaccine candidates.PloS one · 2025Article
- TPepRet: a deep learning model for characterizing T-cell receptors-antigen binding patterns.Bioinformatics (Oxford, England) · 2024Article
- Design, Development and Immunogenicity Study of a Multi-Epitope Vaccine Prototype Against SARS-CoV-2.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Designing a multi-epitope influenza vaccine: an immunoinformatics approach.Scientific reports · 2024Article
- Intranasal Multiepitope PD-L1-siRNA-Based Nanovaccine: The Next-Gen COVID-19 Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Allergies to Allergens from Cats and Dogs: A Review and Update on Sources, Pathogenesis, and Strategies.International journal of molecular sciences · 2024Review
- Multi-epitope vaccines: a promising strategy against viral diseases in swine.Frontiers in cellular and infection microbiology · 2024Review
- Design and computational analysis of an effective multi-epitope vaccine candidate using subunit B of cholera toxin as a build-in adjuvant against urinary tract infections.BioImpacts : BI · 2024Article
- Integrating machine learning to advance epitope mapping.Frontiers in immunology · 2024Review
- Design of a novel multiepitope vaccine against Chlamydia pneumoniae using the extracellular protein as a target.Scientific reports · 2023Article
- Characterization and expression of domains of Alphaherpesvirus bovine 1/5 envelope glycoproteins B in Komagataella phaffi.BMC veterinary research · 2023Article
- Review
- Review
- Peptide-based vaccine for cancer therapies.Frontiers in immunology · 2023Review
- Design of Linear B Cell Epitopes and Evaluation of Their Antigenicity, Allergenicity, and Toxicity: An Immunoinformatics Approach.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Review on Approved and Inprogress COVID-19 Vaccines.Iranian journal of pharmaceutical research : IJPR · 2022Review
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe main processing pathway for MHC class I ligands involves degradation of proteins by the proteasome, followed by transport of products by the transporter associated with antigen processing (TAP) to the endoplasmic reticulum (ER), where peptides are bound by MHC class I molecules, and then presented on the cell surface by MHCs. The whole process is modeled here using an integrated approach, which we call EpiJen. EpiJen is based on quantitative matrices, derived by the additive method, and applied successively to select epitopes. EpiJen is available free online.
resultsTo identify epitopes, a source protein is passed through four steps: proteasome cleavage, TAP transport, MHC binding and epitope selection. At each stage, different proportions of non-epitopes are eliminated. The final set of peptides represents no more than 5% of the whole protein sequence and will contain 85% of the true epitopes, as indicated by external validation. Compared to other integrated methods (NetCTL, WAPP and SMM), EpiJen performs best, predicting 61 of the 99 HIV epitopes used in this study.
conclusionEpiJen is a reliable multi-step algorithm for T cell epitope prediction, which belongs to the next generation of in silico T cell epitope identification methods. These methods aim to reduce subsequent experimental work by improving the success rate of epitope prediction.
Indexed as
Identifiers
What OpenQuestion holds
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.