ArticleBMC bioinformatics2009
NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 277 papers, 2 of them syntheses that pooled it.
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
277 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- In silico design of a T-cell epitope vaccine candidate for parasitic helminth infection.PLoS pathogens · 2020Pooled it
- Structural Basis for CD4+ T Cell Epitope Dominance in Arbo-Flavivirus Envelope Proteins: A Meta-Analysis.Viral immunology · 2017Pooled it
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Immunogenic implications of translational readthrough modulate the association of F8 nonsense mutations with inhibitors in Hemophilia A.Molecular medicine (Cambridge, Mass.) · 2026Article
- In-silico design of a multi-epitope vaccine candidate against Strongyloides stercoralis.BMC infectious diseases · 2026Article
- Designing a novel and effective multi-epitope subunit vaccine against human astrovirus using reverse vaccinology approach.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026Article
- GAMMA: gap-aware motif mining under incomplete labeling with applications to MHC motifs.Bioinformatics (Oxford, England) · 2026Article
- Beyond natural amino acids: extending immunogenicity risk assessment to modified peptides through chemical feature encoding. A case study on citrullination.Frontiers in immunology · 2026Article
- Review: application and opportunities for machine learning and artificial intelligence in preclinical immunogenicity risk assessment.Frontiers in immunology · 2026Review
- Non-Coding DNA-Derived Mimotopes of Aβ₄₂ as Novel Candidates for Alzheimer's Peptide Vaccine Design.International journal of medical sciences · 2026Article
- Optimized Multi-Epitope Norovirus Vaccines Induce Robust Humoral and Cellular Responses in Mice.Vaccines · 2025Article
- Reverse vaccinology-based identification of immunogenic membrane proteins from zoonotic multidrug-resistant Proteus vulgaris: a one health approach to cross-species vaccine development.BMC veterinary research · 2025Article
- Computational Methods in Immunoinformatics: Epitope Discovery and Diagnostic Applications.ACS omega · 2025Review
- Peptides Derived from α-Tubulin Induce Functional T Regulatory Cells.International journal of molecular sciences · 2025Article
- Identification of Coccidioidomycosis Immunoreactive Peptides That Recall T-Cell Responses Indicating Past Exposure.The Journal of infectious diseases · 2025Article
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- Strategies for neoantigen screening and immunogenicity validation in cancer immunotherapy (Review).International journal of oncology · 2025Review
- Machine learning approaches enable the discovery of therapeutics across domains.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Review
- Immunoinformatic strategy for developing multi-epitope subunit vaccine against Helicobacter pylori.PloS one · 2025Article
217 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
2 authors.
Funding
Abstract
backgroundThe major histocompatibility complex (MHC) molecule plays a central role in controlling the adaptive immune response to infections. MHC class I molecules present peptides derived from intracellular proteins to cytotoxic T cells, whereas MHC class II molecules stimulate cellular and humoral immunity through presentation of extracellularly derived peptides to helper T cells. Identification of which peptides will bind a given MHC molecule is thus of great importance for the understanding of host-pathogen interactions, and large efforts have been placed in developing algorithms capable of predicting this binding event.
resultsHere, we present a novel artificial neural network-based method, NN-align that allows for simultaneous identification of the MHC class II binding core and binding affinity. NN-align is trained using a novel training algorithm that allows for correction of bias in the training data due to redundant binding core representation. Incorporation of information about the residues flanking the peptide-binding core is shown to significantly improve the prediction accuracy. The method is evaluated on a large-scale benchmark consisting of six independent data sets covering 14 human MHC class II alleles, and is demonstrated to outperform other state-of-the-art MHC class II prediction methods.
conclusionThe NN-align method is competitive with the state-of-the-art MHC class II peptide binding prediction algorithms. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCII-2.0.
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.