ReviewInternational journal of molecular sciences2021
Linear B-Cell Epitope Prediction for In Silico Vaccine Design: A Performance Review of Methods Available via Command-Line Interface.
Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.
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Who cites it
82 citing papers in PubMed, 121 citations in OpenAlex.
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- Immuno-Informatics Design of Multi-Epitope Vaccine Candidate AgainstHealth science reports · 2026Article
- Immunoinformatics-driven multi-epitope vaccine design as a promising strategy against multidrug-resistant pathogens: a comprehensive review.Folia microbiologica · 2026Review
- Characterization of GH18 chitinase in Leishmania braziliensis: expression, structural insights, and implications for vaccine and therapeutic development.Biological research · 2026Article
- Preparation and Epitope Identification of Monoclonal Antibodies Against African Swine Fever Virus pE120R.Veterinary sciences · 2026Article
- In Silico Design and Characterization of the Essential Outer-Membrane Lipoprotein LolB-Derived Multi-Epitope Vaccine Candidate AgainstMethods and protocols · 2026Article
- Bioinformatics-guided vaccine targeting the hemagglutinin protein of avian influenza virus.Molecular genetics and genomics : MGG · 2026Article
- AntiPan: a genome-informed in silico pipeline for advancing subunit vaccine discovery against Staphylococcus aureus.Scientific reports · 2026Article
- B-cell epitope prediction in the age of machine learning: advancements and challenges.Journal of translational medicine · 2026Review
- PEPNet: a two-stage point cloud framework with hierarchical embedding and antigen-antibody interaction modeling for epitope prediction.Briefings in bioinformatics · 2026Article
- Immunoproteomics: The Evolution from Classical Methods to Emerging Techniques.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Artificial intelligence advancements in monoclonal antibody development technology.Frontiers in immunology · 2026Review
- Reverse vaccinology and immunoinformatics-driven design of a multiepitope vaccine candidate againstFrontiers in bioinformatics · 2026Article
- Grouped immunogens are hierarchically recognized by host to generate antibodies.Frontiers in immunology · 2026Article
- Pangenome-Guided Reverse Vaccinology and Immunoinformatics Approach for Rational Design of a Multi-Epitope Subunit Vaccine Candidate Against the Multidrug-Resistant PathogenPharmaceuticals (Basel, Switzerland) · 2025Article
- B-EPIC: A Transformer-Based Language Model for Decoding B Cell Immunodominance Patterns.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Computational Methods in Immunoinformatics: Epitope Discovery and Diagnostic Applications.ACS omega · 2025Review
- Unlocking Hope: Paving the Way for a Cutting-Edge Multi-Epitope Dengue Virus Vaccine.Molecular biotechnology · 2025Article
- Pepscan and bioinformatic strategies for identification of potential B-cell epitopes for a peptide-based vaccine for tick control.Molecular and biochemical parasitology · 2025Article
- Design of a multi-Epitope mRNA vaccine against Brucella type IV secretion system using reverse vaccinology and immunogenicity approaches.Scientific reports · 2025Article
22 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Linear B-cell epitope prediction research has received a steadily growing interest ever since the first method was developed in 1981. B-cell epitope identification with the help of an accurate prediction method can lead to an overall faster and cheaper vaccine design process, a crucial necessity in the COVID-19 era. Consequently, several B-cell epitope prediction methods have been developed over the past few decades, but without significant success. In this study, we review the current performance and methodology of some of the most widely used linear B-cell epitope predictors which are available via a command-line interface, namely, BcePred, BepiPred, ABCpred, COBEpro, SVMTriP, LBtope, and LBEEP. Additionally, we attempted to remedy performance issues of the individual methods by developing a consensus classifier, which combines the separate predictions of these methods into a single output, accelerating the epitope-based vaccine design. While the method comparison was performed with some necessary caveats and individual methods might perform much better for specialized datasets, we hope that this update in performance can aid researchers towards the choice of a predictor, for the development of biomedical applications such as designed vaccines, diagnostic kits, immunotherapeutics, immunodiagnostic tests, antibody production, and disease diagnosis and therapy.
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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.