ArticleJournal of biomedicine & biotechnology2010
Vaxign: the first web-based vaccine design program for reverse vaccinology and applications for vaccine development.
Article in Journal of biomedicine & biotechnology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 173 papers, 1 of them a synthesis that pooled it.
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
173 citing papers in PubMed, 1 synthesis or guideline pooled it, 357 citations in OpenAlex.
- COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning.Frontiers in immunology · 2020Pooled it
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- In silico design and evaluation of a candidate multiepitope Salmonella vaccine construct targeting broad-spectrum protection in poultry.BMC genomics · 2026Article
- AntiPan: a genome-informed in silico pipeline for advancing subunit vaccine discovery against Staphylococcus aureus.Scientific reports · 2026Article
- Integrating protein language and geometric deep learning models for enhanced vaccine antigen prediction.Nature communications · 2025Article
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- Neoantigen-based immunotherapy: advancing precision medicine in cancer and glioblastoma treatment through discovery and innovation.Exploration of targeted anti-tumor therapy · 2025Review
- A descriptor-free machine learning framework to improve antigen discovery for bacterial pathogens.PloS one · 2025Article
- Melioidosis vaccines: recent advances and future directions.Frontiers in immunology · 2025Review
- In silico construction of a multi-epitope vaccine (RGME-VAC/ATS-1) against the Rickettsia genus using immunoinformatics.Memorias do Instituto Oswaldo Cruz · 2025Article
- Computational Strategies in Drug Discovery: Leveraging Subtractive Genomic Analysis for Target Identification.Current pharmaceutical biotechnology · 2025Review
- Advances of computational methods enhance the development of multi-epitope vaccines.Briefings in bioinformatics · 2024Review
- Immunoinformatics Design of a Multiepitope Vaccine (MEV) TargetingPathogens (Basel, Switzerland) · 2024Article
- Enhancing Vaxign-DL for Vaccine Candidate Prediction with added ESM-Generated Features.bioRxiv : the preprint server for biology · 2024Article
113 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 at 1 institution in 1 country.
Funding
Abstract
Vaxign is the first web-based vaccine design system that predicts vaccine targets based on genome sequences using the strategy of reverse vaccinology. Predicted features in the Vaxign pipeline include protein subcellular location, transmembrane helices, adhesin probability, conservation to human and/or mouse proteins, sequence exclusion from genome(s) of nonpathogenic strain(s), and epitope binding to MHC class I and class II. The precomputed Vaxign database contains prediction of vaccine targets for >70 genomes. Vaxign also performs dynamic vaccine target prediction based on input sequences. To demonstrate the utility of this program, the vaccine candidates against uropathogenic Escherichia coli (UPEC) were predicted using Vaxign and compared with various experimental studies. Our results indicate that Vaxign is an accurate and efficient vaccine design program.
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.