ArticleBriefings in bioinformatics2025
Intelligent Batch Epitope Identification and Partitioning: an intelligent tool for the identification of B cell dominant epitopes.
Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Intelligent antigen design combined with yeast display enhances targeted immune responses.Briefings in bioinformatics · 2026Article
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
Identifying B cell dominant epitopes helps to improve vaccine design and better understand immune evasion of pathogens. Herein, we present the Intelligent Batch Epitope Identification and Partitioning (IBEIP), an intelligent tool for identifying B cell dominant epitope regions based on antigen-neutralizing antibody (Ag-nAb) complex data. IBEIP can accurately map the epitopes on any appointed Ag-nAb complex by analyzing antigen-antibody interactions at a molecular level. Combined with a hierarchical iterative merging model, IBEIP can intelligently merge and analyze mapped epitopes to identify B cell dominant epitopes. It is also applicable to analyzing high-mutant antigens and complex epitope structures. We demonstrated the performance of IBEIP by analyzing 127 Ag-nAb complexes from the respiratory syncytial virus (RSV) fusion, SARS-CoV-2 spike, and high-mutant influenza hemagglutinin. Over 90% of the residues overlapped between IBEIP and reported epitopes, confirming its reliability. IBEIP also uncovered new and important B cell dominant epitope regions and structures of these pathogens for researchers. Our study provides a reliable, intelligent tool for B cell dominant epitope analysis and offers some valuable insights for preventing RSV, SARS-CoV-2, and influenza infections.
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.