ArticleNPJ vaccines2024
The dengue-specific immune response and antibody identification with machine learning.
Article in NPJ vaccines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 17 citations in OpenAlex.
- Signatures of the neutralizing dengue virus-reactive memory B cell repertoire identified by multiplexed envelope dimer probes.medRxiv : the preprint server for health sciences · 2026Article
- Medical software for precision diagnostics of infection with immunoprofiling and artificial intelligence.Journal of translational medicine · 2026Review
- Discovery of Anti-SARS-CoV-2 XBB.1.5 and JN.1 Variant-Specific Monoclonal Single-Domain Antibodies from a Synthetic Library.Antibodies (Basel, Switzerland) · 2026Article
- Leveraging a Meta-Learning Strategy to Advance the Accuracy of Neutralizing Antibodies against Dengue Virus Serotype Prediction.ACS omega · 2025Article
- Accurate identification of broadly neutralizing antibodies against dengue virus based on deep stacking strategy with multi-perspective features.Scientific reports · 2025Article
- Machine learning in AIRR diagnostics: Advances and applications.Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- Review
- Is the vaccination-induced B cell receptor repertoire predictable?Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- Machine Learning and Artificial Intelligence for Infectious Disease Surveillance, Diagnosis, and Prognosis.Viruses · 2025Review
- Article
- Contrasted modifications of IgM and IgT repertoires induced by high- and low-virulent infectious pancreatic necrosis virus strains in rainbow trout (Frontiers in immunology · 2025Article
- Understanding Viral Haemorrhagic Fevers: Virus Diversity, Vector Ecology, and Public Health Strategies.Pathogens (Basel, Switzerland) · 2024Review
- Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes.Scientific reports · 2024Article
- Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling.NPJ systems biology and applications · 2024Article
- High throughput long-read sequencing of circulating lymphocytes of the evolutionarily distant sea lamprey reveals diversity and common elements of the variable lymphocyte receptor B (VLRB) repertoire.Frontiers in immunology · 2024Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
8 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.
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.